Tag #using
13251 papers:
PADL-2020-BrikX #pipes and filters- Diagnosing Data Pipeline Failures Using Action Languages: A Progress Report (AB, JX), pp. 73–81.
- PADL-2020-ChanC #distance #edit distance #flexibility #graph #programming #set
- Flexible Graph Matching and Graph Edit Distance Using Answer Set Programming (SCC, JC), pp. 20–36.
- PADL-2020-ShakerinG #induction #mining
- Whitebox Induction of Default Rules Using High-Utility Itemset Mining (FS, GG), pp. 168–176.
POPL-2020-AnSMS #relational #synthesis- Augmented example-based synthesis using relational perturbation properties (SA, RS, SM, RS), p. 24.
ASPLOS-2020-HildebrandKTLA #automation #integer #linear #memory management #named #programming- AutoTM: Automatic Tensor Movement in Heterogeneous Memory Systems using Integer Linear Programming (MH, JK, ST, JLP, VA), pp. 875–890.
- ASPLOS-2020-LimN #hardware #optimisation #performance
- Optimizing Nested Virtualization Performance Using Direct Virtual Hardware (JTL, JN), pp. 557–574.
- ASPLOS-2020-Mathur0 #linear
- Atomicity Checking in Linear Time using Vector Clocks (UM, MV0), pp. 183–199.
- ASPLOS-2020-YangGLSPNBCHRKH #named #scheduling
- Interstellar: Using Halide's Scheduling Language to Analyze DNN Accelerators (XY, MG, QL, JS, JP, AN, SB, KC, HH, PR, CK, MH), pp. 369–383.
CC-2020-FegadeW #analysis #data type #modelling #pointer #scalability #semantics- Scalable pointer analysis of data structures using semantic models (PF, CW), pp. 39–50.
- CC-2020-PuriniBCB #analysis #image #pipes and filters #smt
- Bitwidth customization in image processing pipelines using interval analysis and SMT solvers (SP, VB, ZC, UB), pp. 167–178.
CGO-2020-JavanmardAKPCH #algorithm #compilation #divide and conquer #multi #parametricity #programming #recursion- Deriving parametric multi-way recursive divide-and-conquer dynamic programming algorithms using polyhedral compilers (MMJ, ZA, MK, LNP, RC, RJH), pp. 317–329.
- CGO-2020-ShobakiKM #approach #combinator #gpu #optimisation
- Optimizing occupancy and ILP on the GPU using a combinatorial approach (GS, AK, SM), pp. 133–144.
EDM-2019-ArthursSKP #modelling- Grades are not Normal: Improving Exam Score Models Using the Logit-Normal Distribution (NA, BS, SK, CP).
- EDM-2019-BanjadeR #logic #probability #student #tutorial
- Assessing Student Response in Tutorial Dialogue Context using Probabilistic Soft Logic (RB, VR).
- EDM-2019-GruverMCPSP #modelling
- Using Latent Variable Models to Observe Academic Pathways (NG, AM, BC, CP, MLS, AP).
- EDM-2019-GuoB #analysis #collaboration #detection
- Collaboration Analysis Using Object Detection (ZG, RB).
- EDM-2019-HarrakBL #approach #categorisation #hybrid #student
- Categorizing students' questions using an ensemble hybrid approach (FH, FB, VL).
- EDM-2019-HicksCL #analysis #process #student
- Students' Use of Support Functions in DBAs: Analysis of NAEP Grade 8 Mathematics Process Data (JH, RC, M(L).
- EDM-2019-HowlinD #approach #behaviour #clustering #detection #fuzzy #student
- Detecting Outlier Behaviors in Student Progress Trajectories Using a Repeated Fuzzy Clustering Approach (CPH, CDD).
- EDM-2019-HuangBS #collaboration #identification #machine learning
- Identifying Collaborative Learning States Using Unsupervised Machine Learning on Eye-Tracking, Physiological and Motion Sensor Data (KH, TB, BS).
- EDM-2019-Ikeda #analysis #education #learning #quality
- Learning Feature Analysis for Quality Improvement of Web-Based Teaching Materials Using Mouse Cursor Tracking (MI).
- EDM-2019-JayaramanGG #identification #machine learning #student
- Supporting Minority Student Success by using Machine Learning to Identify At-Risk Students (JDJ, SG, JG).
- EDM-2019-JeonSBLR #online #process #student
- Time-series Insights into the Process of Passing or Failing Online University Courses using Neural-Induced Interpretable Student States (BJ, ES, LB, JL, CPR).
- EDM-2019-MalekianBKBN #analysis #process #student
- Characterising Students' Writing Processes Using Temporal Keystroke Analysis (DM, JB0, GEK, PGdB, SN).
- EDM-2019-NguyenWSM #component #comprehension #game studies #learning #modelling
- Using Knowledge Component Modeling to Increase Domain Understanding in a Digital Learning Game (HN, YW, JCS, BMM).
- EDM-2019-RamirezYCRS #learning #student #towards
- Toward Instrumenting Makerspaces: Using Motion Sensors to Capture Students' Affective States in Open-Ended Learning Environments (LR, WY, EC, IR, BS).
- EDM-2019-Reddick #algorithm #learning
- Using a Glicko-based Algorithm to Measure In-Course Learning (RR).
- EDM-2019-Sher #learning #mobile
- Anatomy of mobile learners: Using learning analytics to unveil learning in presence of mobile devices (VS).
- EDM-2019-Unal #composition #modelling #performance #student
- Modeling Student Performance and Disengagement Using Decomposition of Response Time Data (DSU).
- EDM-2019-WampflerKSSG #mobile #predict #smarttech
- Affective State Prediction in a Mobile Setting using Wearable Biometric Sensors and Stylus (RW, SK, BS, VRS, MG0).
- EDM-2019-WeitekampHMRK #learning #predict #student #towards
- Toward Near Zero-Parameter Prediction Using a Computational Model of Student Learning (DWI, EH, CJM, NR, KRK).
- EDM-2019-YahyaMO #data mining #education #effectiveness #mining #novel #source code
- A Novel Use of Educational Data Mining to Inform Effective Management of Academic Programs (AAY, FAM, AO).
- EDM-2019-Yeung #learning #named
- Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory (CKY).
- EDM-2019-ZaidiCDMBR #learning #modelling #student
- Accurate Modelling of Language Learning Tasks and Students Using Representations of Grammatical Proficiency (AHZ, AC, CD, RM, PB, AR).
ICPC-2019-AlrubayeM0 #detection #information retrieval #java #library #migration #on the- On the use of information retrieval to automate the detection of third-party Java library migration at the method level (HA, MWM, AO0), pp. 347–357.
- ICPC-2019-FontanaP #debugging #sequence #visualisation
- Visualizing sequences of debugging sessions using swarm debugging (EAF, FP), pp. 139–143.
- ICPC-2019-FucciGNQL #comprehension #lightweight #replication
- A replication study on code comprehension and expertise using lightweight biometric sensors (DF, DG, NN, LQ, FL), pp. 311–322.
- ICPC-2019-KuangG0M0ME #analysis #feedback #traceability
- Using frugal user feedback with closeness analysis on code to improve IR-based traceability recovery (HK, HG, HH0, XM, JL0, PM, AE), pp. 369–379.
- ICPC-2019-MizouchiSII #adaptation #detection #named #online
- PADLA: a dynamic log level adapter using online phase detection (TM, KS, TI, KI), pp. 135–138.
ICSME-2019-AungHS #interactive #traceability #visualisation- Interactive Traceability Links Visualization using Hierarchical Trace Map (TWWA, HH, YS), pp. 367–369.
- ICSME-2019-PalacioMMBPS #identification #learning #network
- Learning to Identify Security-Related Issues Using Convolutional Neural Networks (DNP, DM, KM, CBC, DP, CS), pp. 140–144.
- ICSME-2019-ShimariI0I #debugging #execution #java
- Near-Omniscient Debugging for Java Using Size-Limited Execution Trace (KS, TI, TK0, KI), pp. 398–401.
MSR-2019-DamPN0GGKK #fault #lessons learnt #predict- Lessons learned from using a deep tree-based model for software defect prediction in practice (HKD, TP, SWN, TT0, JCG, AG, TK, CJK), pp. 46–57.
- MSR-2019-EfstathiouS #identifier #modelling #semantics #source code
- Semantic source code models using identifier embeddings (VE, DS), pp. 29–33.
- MSR-2019-KiehnPC #classification #empirical #version control
- Empirical study in using version histories for change risk classification (MK, XP, FC), pp. 58–62.
- MSR-2019-LiuLZFDQ #commit #generative #network
- Generating commit messages from diffs using pointer-generator network (QL, ZL, HZ, HF, BD, YQ), pp. 299–309.
SANER-2019-KirinukiTN #named #recommendation #testing #web- COLOR: Correct Locator Recommender for Broken Test Scripts using Various Clues in Web Application (HK, HT, KN), pp. 310–320.
- SANER-2019-MuscedereHAADG #analysis #detection #lightweight
- Detecting Feature-Interaction Symptoms in Automotive Software using Lightweight Analysis (BJM, RH, DA, JMA, IJD, MWG), pp. 175–185.
- SANER-2019-SunBBS #documentation #mining #specification
- Mining Specifications from Documentation using a Crowd (PS, CB, IB, KTS), pp. 275–286.
- SANER-2019-VerhaegheEASDDD #case study #industrial #migration #user interface
- GUI Migration using MDE from GWT to Angular 6: An Industrial Case (BV, AE, NA, AS, LD, SD, MD), pp. 579–583.
- SANER-2019-ZhangLML #approach #effectiveness #fault #named #network
- CNN-FL: An Effective Approach for Localizing Faults using Convolutional Neural Networks (ZZ0, YL, XM, PL), pp. 445–455.
SCAM-2019-HendersonPK #automation #fault #locality #markov #process- Evaluating Automatic Fault Localization Using Markov Processes (TADH, AP, YK), pp. 115–126.
- SCAM-2019-MasudC #towards
- Towards Constructing the SSA form using Reaching Definitions Over Dominance Frontiers (ANM, FC), pp. 23–33.
- SCAM-2019-MondalRS #analysis #architecture #automation #case study #natural language
- An Exploratory Study on Automatic Architectural Change Analysis Using Natural Language Processing Techniques (AKM, BR, KAS), pp. 62–73.
- SCAM-2019-PerumaMDN #commit #refactoring
- Contextualizing Rename Decisions using Refactorings and Commit Messages (AP, MWM, MJD, CDN), pp. 74–85.
FM-2019-BardBD #fault #smt- Formally Verified Roundoff Errors Using SMT-based Certificates and Subdivisions (JB, HB, ED), pp. 38–44.
- FM-2019-GomesB19a #csp #model checking #named
- Circus2CSP: A Tool for Model-Checking Circus Using FDR (AOG, AB), pp. 235–242.
- FM-2019-SilveiraJVJ #formal method #implementation #specification
- Formal Methods Applicability on Space Applications Specification and Implementation Using MORA-TSP (DS, AJ, MV, TJ), pp. 727–737.
- IFM-2019-BenesBGPS #algebra #constraints #parametricity #synthesis
- Accelerating Parameter Synthesis Using Semi-algebraic Constraints (NB, LB, MG, SP, DS), pp. 27–45.
- IFM-2019-BruckerW #certification #ontology
- Using Ontologies in Formal Developments Targeting Certification (ADB, BW), pp. 65–82.
- IFM-2019-LutebergetCJ #automation #optimisation #satisfiability
- Automated Drawing of Railway Schematics Using Numerical Optimization in SAT (BL, KC, CJ), pp. 341–359.
SEFM-2019-BeckertBGHLU #relational #slicing #verification- Using Relational Verification for Program Slicing (BB, TB, SG, MH, DL, MU), pp. 353–372.
- SEFM-2019-FarrellBFDDYM #analysis #case study #verification
- Using Threat Analysis Techniques to Guide Formal Verification: A Case Study of Cooperative Awareness Messages (MF, MB, MF0, LAD, CD, HY, CM), pp. 471–490.
- ICFP-2019-HameerP #automation #case study #education #experience #functional #programming
- Teaching the art of functional programming using automated grading (experience report) (AH, BP), p. 15.
AIIDE-2019-BehroozRJ #matter #quality #word- Story Quality as a Matter of Perception: Using Word Embeddings to Estimate Cognitive Interest (MB, JR, AJ), pp. 3–9.
- AIIDE-2019-Sanghrajka #authoring #interactive #modelling
- Interactive Narrative Authoring Using Cognitive Models in Narrative Planning (RS), pp. 224–226.
- AIIDE-2019-Shirvani #towards
- Towards More Believable Characters Using Personality and Emotion (AS), pp. 230–232.
CHI-PLAY-2019-SchertlerKW #analysis #game studies #semantics- User Guided Movement Analysis in Games using Semantic Trajectories (RS, SK, GW), pp. 613–623.
CoG-2019-Aitchison #experience- Optimal Use of Experience in First Person Shooter Environments (MA), pp. 1–4.
- CoG-2019-ChangAS #assurance #automation #named #quality #testing
- Reveal-More: Amplifying Human Effort in Quality Assurance Testing Using Automated Exploration (KC, BA, AMS), pp. 1–8.
- CoG-2019-ChristiansenGW #bias #game studies
- Resolving Simultaneity Bias: Using Features to Estimate Causal Effects in Competitive Games (AHC, EG, BSW), pp. 1–8.
- CoG-2019-Eidelberg0D #game studies #performance
- Using Active Probing by a Game Management AI to Faster Classify Players (AE, CJ0, JD), pp. 1–8.
- CoG-2019-FendtA #education #game studies #learning #student
- Using Learning Games to Teach Texas Civil War History to Public Middle School Students (MWF, EA), pp. 1–4.
- CoG-2019-IshiiITH #game studies #generative
- A Fighting Game AI Using Highlight Cues for Generation of Entertaining Gameplay (RI, SI, RT, TH), pp. 1–6.
- CoG-2019-JooK #game studies #how #learning #question #visualisation
- Visualization of Deep Reinforcement Learning using Grad-CAM: How AI Plays Atari Games? (HTJ, KJK), pp. 1–2.
- CoG-2019-JoppenSF #approximate #game studies
- Ordinal Bucketing for Game Trees using Dynamic Quantile Approximation (TJ, TS, JF), pp. 1–8.
- CoG-2019-KatonaSHDBDW #learning #predict
- Time to Die: Death Prediction in Dota 2 using Deep Learning (AK, RJS, VJH, SD, FB, AD, JAW), pp. 1–8.
- CoG-2019-KimLLHK #algorithm #automation #game studies #generative #graph
- Automatic Generation of Game Content using a Graph-based Wave Function Collapse Algorithm (HK, SL, HL, TH, SK), pp. 1–4.
- CoG-2019-KusanoLPTH #game studies
- Motion Gaming AI using Time Series Forecasting and Dynamic Difficulty Adjustment (TK, YL, PP, RT, TH), pp. 1–6.
- CoG-2019-Lanzi #complexity
- Evaluating the Complexity of Players' Strategies using MCTS Iterations (PLL), pp. 1–8.
- CoG-2019-LipinskiSRA #generative #graph #incremental
- Level Graph - Incremental Procedural Generation of Indoor Levels using Minimum Spanning Trees (BvRL, SS, JR, DA), pp. 1–7.
- CoG-2019-LiuR0S #heuristic #performance
- Using Restart Heuristics to Improve Agent Performance in Angry Birds (TL, JR, PZ0, MS), pp. 1–8.
- CoG-2019-MassoudBBGP #behaviour #game studies #profiling
- Eco-driving Profiling and Behavioral Shifts Using IoT Vehicular Sensors Combined with Serious Games (RM, FB, RB, ADG, SP), pp. 1–8.
- CoG-2019-NamI #game studies #generative #learning
- Generation of Diverse Stages in Turn-Based Role-Playing Game using Reinforcement Learning (SN, KI), pp. 1–8.
- CoG-2019-NygrenD #case study #concept #game studies #self
- Using Simple Games to Evaluate Self-Organization Concepts: a Whack-a-mole Case Study (NN, JD), pp. 1–8.
- CoG-2019-SarkarC #game studies
- Inferring and Comparing Game Difficulty Curves using Player-vs-Level Match Data (AS, SC), pp. 1–4.
- CoG-2019-SpickCW #generative #learning
- Procedural Generation using Spatial GANs for Region-Specific Learning of Elevation Data (RJS, PC, JAW), pp. 1–8.
FDG-2019-GandhiH #generative #modelling #probability #visual notation- Guided open story generation using probabilistic graphical models (SG, BH), p. 7.
- FDG-2019-JemmaliKBARE #concept #design #game studies #learning #programming
- Using game design mechanics as metaphors to enhance learning of introductory programming concepts (CJ, EK, SB, MVA, ER, MSEN), p. 5.
- FDG-2019-LiGH #game studies #generative #multi #video
- End-to-end let's play commentary generation using multi-modal video representations (CL0, SG, BH), p. 7.
- FDG-2019-LiuLLMHSWCGLDT #automation #generative
- Automatic generation of tower defense levels using PCG (SCL, CL, YL, HM, XH, YS, LW, ZC, XG, HL, YD, QT), p. 9.
- FDG-2019-LuoGR #network #parsing #video
- Making CNNs for video parsing accessible: event extraction from DOTA2 gameplay video using transfer, zero-shot, and network pruning (ZL, MG, MR), p. 10.
- FDG-2019-MacCormickZ #development #game studies #named #programming #visual notation
- SuBViS: the use of subjunctive visual programming environments for exploring alternatives in game development (DM, LZ), p. 11.
- FDG-2019-OuelletteBC #analysis #comprehension #design #education #game studies
- Using applied cognitive load theory and difficulty analysis for educational game design for understanding and transference of literacy skills in adults (MO, LB, CC), p. 11.
- FDG-2019-SarkarC #array #rating
- Using rating arrays to estimate score distributions for player-versus-level matchmaking (AS, SC), p. 8.
- VS-Games-2019-BakalosRDDPV #identification #network
- Choreographic Pose Identification using Convolutional Neural Networks (NB, IR, ND, AD, EP, AV), pp. 1–7.
- VS-Games-2019-Gabriel #concept #design #game studies
- We Make Games. Using Serious Game Design Concepts in Secondary School (SG), pp. 1–4.
- VS-Games-2019-HeinzS #design #evaluation #heuristic #simulation
- Addressing Spatio-Temporal Geogame Relocation Issues Using Design Evaluation Heuristics and Agent-based Simulation (TH0, CS), pp. 1–4.
- VS-Games-2019-KharvariH #3d #architecture #artificial reality #game studies #visualisation
- The Role of Serious Gaming using Virtual Reality Applications for 3D Architectural Visualization (FK, WH), pp. 1–2.
- VS-Games-2019-KicoL #comparison
- Comparison of Trajectories and Quaternions of Folk Dance Movements Using Dynamic Time Warping (IK, FL), pp. 1–4.
CIKM-2019-ChristmannRASW #graph- Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansion (PC, RSR, AA, JS, GW), pp. 729–738.
- CIKM-2019-DuongRN #multi #sketching #streaming
- Sketching Streaming Histogram Elements using Multiple Weighted Factors (QHD, HR, KN), pp. 19–28.
- CIKM-2019-GongZ00XWH #community #detection #developer #learning #online
- Detecting Malicious Accounts in Online Developer Communities Using Deep Learning (QG, JZ, YC0, QL0, YX, XW, PH), pp. 1251–1260.
- CIKM-2019-HanMNKURNS #detection #image #learning
- Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR Images (CH, KM, TN, YK, FU, LR, HN, SS), pp. 119–127.
- CIKM-2019-IslamMR #graph #named #network #predict #social
- NActSeer: Predicting User Actions in Social Network using Graph Augmented Neural Network (MRI, SM, NR), pp. 1793–1802.
- CIKM-2019-JungLPP #framework #named
- PRIVATA: Differentially Private Data Market Framework using Negotiation-based Pricing Mechanism (KJ, JL, KP, SP), pp. 2897–2900.
- CIKM-2019-KangPKCC #modelling #recommendation #topic
- Recommender System Using Sequential and Global Preference via Attention Mechanism and Topic Modeling (KK, JP, WK, HC, JC), pp. 1543–1552.
- CIKM-2019-LinPLO #network #recognition
- An Explainable Deep Fusion Network for Affect Recognition Using Physiological Signals (JL, SP, CSL, SLO), pp. 2069–2072.
- CIKM-2019-LinWXLB #estimation #hybrid #network
- Path Travel Time Estimation using Attribute-related Hybrid Trajectories Network (XL, YW, XX, ZL, SSB), pp. 1973–1982.
- CIKM-2019-YangWCW #graph #network #predict
- Using External Knowledge for Financial Event Prediction Based on Graph Neural Networks (YY, ZW, QC, LW), pp. 2161–2164.
- CIKM-2019-YanLWLWZG #classification #image #multi #random
- Imbalance Rectification in Deep Logistic Regression for Multi-Label Image Classification Using Random Noise Samples (WY, RL, JW, YL, JW, PZ, XG), pp. 1131–1140.
- CIKM-2019-ZhangL
- Interpretable MTL from Heterogeneous Domains using Boosted Tree (YLZ, LL), pp. 2053–2056.
ECIR-p1-2019-BalikasDMAA #learning #semantics- Learning Lexical-Semantic Relations Using Intuitive Cognitive Links (GB, GD, RM, HA, MRA), pp. 3–18.
- ECIR-p1-2019-DavilaJSGZ #graph #image #named
- Tangent-V: Math Formula Image Search Using Line-of-Sight Graphs (KD, RJ, SS, VG, RZ), pp. 681–695.
- ECIR-p1-2019-GlavasV #bidirectional #retrieval
- Zero-Shot Language Transfer for Cross-Lingual Sentence Retrieval Using Bidirectional Attention Model (GG, IV), pp. 523–538.
- ECIR-p1-2019-JeawakJS #modelling
- Embedding Geographic Locations for Modelling the Natural Environment Using Flickr Tags and Structured Data (SSJ, CBJ, SS), pp. 51–66.
- ECIR-p1-2019-NguyenV
- End-to-End Neural Relation Extraction Using Deep Biaffine Attention (DQN, KV), pp. 729–738.
- ECIR-p1-2019-ZhongZ #similarity
- Structural Similarity Search for Formulas Using Leaf-Root Paths in Operator Subtrees (WZ, RZ), pp. 116–129.
- ECIR-p2-2019-AkbariCBOSW #modelling #process
- Modeling User Return Time Using Inhomogeneous Poisson Process (MA, AC, SB, ADO, MS, JW0), pp. 37–44.
- ECIR-p2-2019-Ghosh #information retrieval
- Exploring Result Presentation in Conversational IR Using a Wizard-of-Oz Study (SG), pp. 327–331.
- ECIR-p2-2019-ImaniVMS19a #network #query #word
- Deep Neural Networks for Query Expansion Using Word Embeddings (AI, AV, AM, AS), pp. 203–210.
- ECIR-p2-2019-PritsosRS #distance #identification #nearest neighbour #web
- Open-Set Web Genre Identification Using Distributional Features and Nearest Neighbors Distance Ratio (DAP, AR0, ES), pp. 3–11.
ICML-2019-ChangMG #metric #scheduling- Dynamic Measurement Scheduling for Event Forecasting using Deep RL (CHC, MM, AG), pp. 951–960.
- ICML-2019-DaoGERR #algorithm #learning #linear #performance
- Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations (TD, AG, ME, AR, CR), pp. 1517–1527.
- ICML-2019-ElfekiCRE #learning #named #process
- GDPP: Learning Diverse Generations using Determinantal Point Processes (ME, CC, MR, ME), pp. 1774–1783.
- ICML-2019-GordalizaBGL
- Obtaining Fairness using Optimal Transport Theory (PG, EdB, FG, JML), pp. 2357–2365.
- ICML-2019-HendrycksLM #nondeterminism #robust
- Using Pre-Training Can Improve Model Robustness and Uncertainty (DH, KL, MM), pp. 2712–2721.
- ICML-2019-HollandI #robust
- Better generalization with less data using robust gradient descent (MJH, KI), pp. 2761–2770.
- ICML-2019-HuntBLH #policy
- Composing Entropic Policies using Divergence Correction (JJH, AB, TPL, NH), pp. 2911–2920.
- ICML-2019-MendisRAC #estimation #named #network #performance #throughput
- Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks (CM, AR, SPA, MC), pp. 4505–4515.
- ICML-2019-Ravi #modelling #performance
- Efficient On-Device Models using Neural Projections (SR), pp. 5370–5379.
- ICML-2019-ThulasidasanBBC #learning
- Combating Label Noise in Deep Learning using Abstention (ST, TB, JAB, GC, JMY), pp. 6234–6243.
- ICML-2019-TranKSK #named #network
- DeepNose: Using artificial neural networks to represent the space of odorants (NBT, DRK, SS, AAK), pp. 6305–6314.
- ICML-2019-TrippeHAB #approximate #named #rank
- LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations (BLT, JHH, RA, TB), pp. 6315–6324.
- ICML-2019-WangDWK #learning #logic #named #reasoning #satisfiability
- SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver (PWW, PLD, BW, JZK), pp. 6545–6554.
- ICML-2019-X #bound #named #policy #predict
- POLITEX: Regret Bounds for Policy Iteration using Expert Prediction, pp. 3692–3702.
- ICML-2019-YangW #parametricity
- Sample-Optimal Parametric Q-Learning Using Linearly Additive Features (LY, MW), pp. 6995–7004.
- ICML-2019-ZanetteB #bound #learning #problem
- Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds (AZ, EB), pp. 7304–7312.
- ICML-2019-ZhaoHDSZ #network
- Improving Neural Network Quantization without Retraining using Outlier Channel Splitting (RZ, YH, JD, CDS, ZZ), pp. 7543–7552.
KDD-2019-ChenLPS #predict #twitter- Using Twitter to Predict When Vulnerabilities will be Exploited (HC0, RL, NP, VSS), pp. 3143–3152.
- KDD-2019-ChenSJ0Z0 #behaviour #effectiveness #performance #recommendation #reuse
- Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation (LC, SS, CSJ, BY0, ZZ, LS0), pp. 488–498.
- KDD-2019-DeshpandeS #adaptation #modelling #streaming
- Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units (PD, SS), pp. 1560–1568.
- KDD-2019-GuoHJZW0 #behaviour #multi #network #predict #realtime
- Buying or Browsing?: Predicting Real-time Purchasing Intent using Attention-based Deep Network with Multiple Behavior (LG, LH, RJ, BZ, XW, BC0), pp. 1984–1992.
- KDD-2019-KillianWSCDT #learning
- Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data (JAK, BW, AS, VC, BD, MT), pp. 2430–2438.
- KDD-2019-KitadaIS #effectiveness #multi #network #predict
- Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives (SK, HI, YS), pp. 2069–2077.
- KDD-2019-LeeIFSM #approach #data-driven #estimation #named
- DeepRoof: A Data-driven Approach For Solar Potential Estimation Using Rooftop Imagery (SL, SI, MF, PJS, SM), pp. 2105–2113.
- KDD-2019-MarxV
- Identifiability of Cause and Effect using Regularized Regression (AM, JV), pp. 852–861.
- KDD-2019-MonathZSMA #clustering
- Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space (NM, MZ, DS, AM, AA), pp. 714–722.
- KDD-2019-OhI #detection #learning
- Sequential Anomaly Detection using Inverse Reinforcement Learning (MhO, GI), pp. 1480–1490.
- KDD-2019-PanLW00Z #learning #predict
- Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning (ZP, YL, WW, YY0, YZ0, JZ), pp. 1720–1730.
- KDD-2019-ParkKDZF #graph #network
- Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks (NP, AK, XLD, TZ, CF), pp. 596–606.
- KDD-2019-RawatLY #learning #multi
- Naranjo Question Answering using End-to-End Multi-task Learning Model (BPSR, FL, HY0), pp. 2547–2555.
- KDD-2019-SchonD0 #fault #how #predict
- The Error is the Feature: How to Forecast Lightning using a Model Prediction Error (CS, JD, RM0), pp. 2979–2988.
- KDD-2019-SchulzeMRLB #identification
- Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy (JPS, AM, ER, HAL, KB), pp. 2059–2068.
- KDD-2019-SheehanMTUJBLE #development #predict #wiki
- Predicting Economic Development using Geolocated Wikipedia Articles (ES, CM, MT, BU, NJ, MB, DBL, SE), pp. 2698–2706.
- KDD-2019-ShenVAAHN #learning #monitoring #smarttech
- Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning (YS, MV, AA, AA, AYH, AYN), pp. 1909–1916.
- KDD-2019-SiciliaPG #named
- DeepHoops: Evaluating Micro-Actions in Basketball Using Deep Feature Representations of Spatio-Temporal Data (AS, KP, KG), pp. 2096–2104.
- KDD-2019-TariqLSLJCW #detection #multi #probability
- Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA (ST, SL, YS, MSL, OJ, DC, SSW), pp. 2123–2133.
- KDD-2019-WangZTWX #named #network
- AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks (JW, YZ0, KT, JW, ZX), pp. 1900–1908.
- KDD-2019-WuYZXZPXA #graph #kernel #random #scalability
- Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding (LW, IEHY, ZZ0, KX, LZ0, XP0, YX, CCA), pp. 1418–1428.
- KDD-2019-YabeTSSU #behaviour #predict #web
- Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior (TY, KT, TS, YS, SVU), pp. 2707–2717.
- KDD-2019-ZhengXKWMAY #linear #predict
- Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression (YZ, LX, TK, JW0, HM, RA, KY), pp. 2278–2286.
- KDD-2019-ZhouMGBB #comprehension #network
- Understanding Consumer Journey using Attention based Recurrent Neural Networks (YZ, SM, JG, TB, NB), pp. 3102–3111.
BX-2019-Tullsen #encoding- ASN.1 Encoding Schemes Done Right Using CMPCT (MT), pp. 1–15.
MoDELS-2019-BencomoP #learning #modelling #named #ram #runtime- RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning (NB, LHGP), pp. 216–226.
- MoDELS-2019-TorreSSBAG #case study #experience #modelling
- Using Models to Enable Compliance Checking Against the GDPR: An Experience Report (DT, GS, MS, LCB, YA, PG), pp. 1–11.
OOPSLA-2019-ChenWFBD #learning #relational #verification- Relational verification using reinforcement learning (JC, JW, YF, OB, ID), p. 30.
- OOPSLA-2019-GoelV #design #implementation #lazy evaluation #on the
- On the design, implementation, and use of laziness in R (AG, JV), p. 27.
- OOPSLA-2019-KrikavaMV #scala #scalability
- Scala implicits are everywhere: a large-scale study of the use of Scala implicits in the wild (FK, HM, JV), p. 28.
- PADL-2019-AriasC #composition #evaluation #incremental #logic programming
- Incremental Evaluation of Lattice-Based Aggregates in Logic Programming Using Modular TCLP (JA, MC), pp. 98–114.
- PADL-2019-KahramanE #personalisation #programming #set
- Personalized Course Schedule Planning Using Answer Set Programming (MKK, EE0), pp. 37–45.
PLDI-2019-0001R #database #learning #modelling- Using active learning to synthesize models of applications that access databases (JS0, MCR), pp. 269–285.
- PLDI-2019-DhulipalaBS #graph #streaming
- Low-latency graph streaming using compressed purely-functional trees (LD, GEB, JS), pp. 918–934.
- PLDI-2019-HeoRSN #difference #reasoning #source code
- Continuously reasoning about programs using differential Bayesian inference (KH, MR, XS, MN), pp. 561–575.
- PLDI-2019-LeZN #dynamic analysis #invariant #logic #named
- SLING: using dynamic analysis to infer program invariants in separation logic (TCL, GZ, TN), pp. 788–801.
- POPL-2019-BaeL #bound #logic #model checking
- Bounded model checking of signal temporal logic properties using syntactic separation (KB, JL), p. 30.
- POPL-2019-CastroHJNY #api #communication #distributed #parametricity #programming #static typing
- Distributed programming using role-parametric session types in go: statically-typed endpoint APIs for dynamically-instantiated communication structures (DCP, RH, SSJ, NN, NY), p. 30.
- POPL-2019-SkorstengaardDB #control flow #encapsulation #linear #named #stack
- StkTokens: enforcing well-bracketed control flow and stack encapsulation using linear capabilities (LS, DD, LB), p. 28.
- POPL-2019-SpathAB #analysis #automaton #data flow
- Context-, flow-, and field-sensitive data-flow analysis using synchronized Pushdown systems (JS, KA0, EB), p. 29.
SAS-2019-DelmasM #abstract interpretation #analysis- Analysis of Software Patches Using Numerical Abstract Interpretation (DD, AM), pp. 225–246.
ASE-2019-Balasubramaniam #machine learning #representation #towards- Towards Comprehensible Representation of Controllers using Machine Learning (GB), pp. 1283–1285.
- ASE-2019-ChenSHWL #behaviour #case study #experience #generative #testing
- An Experience Report of Generating Load Tests Using Log-Recovered Workloads at Varying Granularities of User Behaviour (JC, WS, AEH, YW, JL), pp. 669–681.
- ASE-2019-KimC #embedded #model checking
- Model Checking Embedded Control Software using OS-in-the-Loop CEGAR (DK, YC), pp. 565–576.
- ASE-2019-MehraSKP #artificial reality #named #towards
- XRaSE: Towards Virtually Tangible Software using Augmented Reality (RM, VSS, VK, SP), pp. 1194–1197.
- ASE-2019-NafiKRRS #api #clone detection #detection #documentation #named
- CLCDSA: Cross Language Code Clone Detection using Syntactical Features and API Documentation (KWN, TSK, BR, CKR, KAS), pp. 1026–1037.
- ASE-2019-Ramamoorthy #game studies #multi
- User Preference Aware Multimedia Pricing Model using Game Theory and Prospect Theory for Wireless Communications (KMKR), pp. 1265–1267.
- ASE-2019-Sharma #adaptation #automation #source code #synthesis
- Automatically Repairing Binary Programs Using Adapter Synthesis (VS), pp. 1238–1241.
- ASE-2019-ZhengFXS0HMLSC #automation #game studies #learning #named #online #testing
- Wuji: Automatic Online Combat Game Testing Using Evolutionary Deep Reinforcement Learning (YZ, CF, XX, TS, LM0, JH, ZM, YL0, RS, YC), pp. 772–784.
ESEC-FSE-2019-BarashFJRTZ #feature model #interactive #ml #requirements- Bridging the gap between ML solutions and their business requirements using feature interactions (GB, EF, IJ, OR, RTB, MZ), pp. 1048–1058.
- ESEC-FSE-2019-Cetin #developer #graph #identification #traceability
- Identifying the most valuable developers using artifact traceability graphs (HAC), pp. 1196–1198.
- ESEC-FSE-2019-Correia #industrial #testing
- An industrial application of test selection using test suite diagnosability (DC), pp. 1214–1216.
- ESEC-FSE-2019-CorreiaASN #multi #named #testing
- MOTSD: a multi-objective test selection tool using test suite diagnosability (DC, RA, PS, JN), pp. 1070–1074.
- ESEC-FSE-2019-Denkers #case study #domain-specific language #industrial
- A longitudinal field study on creation and use of domain-specific languages in industry (JD), pp. 1152–1155.
- ESEC-FSE-2019-FucciMM #api #documentation #identification #machine learning #on the
- On using machine learning to identify knowledge in API reference documentation (DF, AM, WM), pp. 109–119.
- ESEC-FSE-2019-LiewCDS #constraints #float #fuzzing
- Just fuzz it: solving floating-point constraints using coverage-guided fuzzing (DL, CC, AFD, JRS), pp. 521–532.
- ESEC-FSE-2019-NguyenSCMBL #as a service #multitenancy
- Using microservices for non-intrusive customization of multi-tenant SaaS (PHN, HS, FC, RM, SB, EL), pp. 905–915.
- ESEC-FSE-2019-Radavelli #modelling #testing
- Using software testing to repair models (MR), pp. 1253–1255.
- ESEC-FSE-2019-SangleM #on the #open source #python
- On the use of lambda expressions in 760 open source Python projects (SS, SM), pp. 1232–1234.
- ESEC-FSE-2019-Sulun #graph #traceability
- Suggesting reviewers of software artifacts using traceability graphs (ES), pp. 1250–1252.
- ICSE-2019-FanLLWNZL #analysis #android #graph #learning
- Graph embedding based familial analysis of Android malware using unsupervised learning (MF, XL, JL0, MW, CN, QZ, TL0), pp. 771–782.
- ICSE-2019-HuangLKSHLW #data type
- Distilling neural representations of data structure manipulation using fMRI and fNIRS (YH0, XL, RK, TS, XH, KL, WW), pp. 396–407.
- ICSE-2019-KimFY #learning #testing
- Guiding deep learning system testing using surprise adequacy (JK, RF, SY), pp. 1039–1049.
- ICSE-2019-ZhangHMBLU #ltl #named #source code
- AutoTap: synthesizing and repairing trigger-action programs using LTL properties (LZ, WH, JM, NB, SL, BU), pp. 281–291.
GPCE-2019-Dimovski #abstract domain #diagrams #static analysis- Lifted static analysis using a binary decision diagram abstract domain (ASD), pp. 102–114.
- ASPLOS-2019-KondguliH #hardware #named #performance #smt #thread
- Bootstrapping: Using SMT Hardware to Improve Single-Thread Performance (SK, MH), pp. 687–700.
- ASPLOS-2019-RenZYLXQLW #co-evolution #design #framework #multi #named
- ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Methods of Multipliers (AR, TZ, SY, JL, WX, XQ, XL, YW), pp. 925–938.
- ASPLOS-2019-WuSCL #pointer
- Protecting Page Tables from RowHammer Attacks using Monotonic Pointers in DRAM True-Cells (XCW, TS, FTC, YL), pp. 645–657.
CASE-2019-AndersonlPL #estimation #mobile #recursion- Mobile Robotic Radiation Surveying Using Recursive Bayesian Estimation (RBA, MP, SL), pp. 1187–1192.
- CASE-2019-AshouriNSG #predict
- Day-ahead Prediction of Building Occupancy using WiFi Signals (AA, GRN, ZS, HBG), pp. 1237–1242.
- CASE-2019-AyoobiCVV #learning
- Handling Unforeseen Failures Using Argumentation-Based Learning (HA, MC0, RV, BV), pp. 1699–1704.
- CASE-2019-BiedigerMB #artificial reality
- Investigating the survivability of drone swarms with flocking and swarming flight patterns using Virtual Reality (DB, AM, ATB), pp. 1718–1723.
- CASE-2019-ChangLH #coordination #detection #network #realtime
- Real-Time Object Coordinate Detection and Manipulator Control Using Rigidly Trained Convolutional Neural Networks (YMC, CHGL, YFH), pp. 1347–1352.
- CASE-2019-ChengT #flexibility #tool support
- Control of a mechatronics-assisted system for surgeries using flexible tools (LC, MT), pp. 1768–1773.
- CASE-2019-ChenLVR #machine learning #process
- Strip Snap Analytics in Cold Rolling Process Using Machine Learning (ZC, YL, AVM, FR), pp. 368–373.
- CASE-2019-DasSAP #estimation #interactive #physics
- Joint Torque Estimation using Base Force-Torque Sensor to Facilitate Physical Human-Robot Interaction (pHRI) (SKD, MNS, SA, DOP), pp. 1367–1372.
- CASE-2019-DuHD #identification #physics
- Model Identification and Physical Exercise Control using Nonlinear Heart Rate Model and Particle Filter (DD, ZH, YD), pp. 405–410.
- CASE-2019-FarooquiF #learning #modelling #synthesis
- Synthesis of Supervisors for Unknown Plant Models Using Active Learning (AF, MF), pp. 502–508.
- CASE-2019-FujitaDKRKSHAFA #multi
- Bin-picking Robot using a Multi-gripper Switching Strategy based on Object Sparseness (MF, YD, RK, GAGR, KK, KS, RH, RA, HF, SA, MH, AJC, AN, HO, TO), pp. 1540–1547.
- CASE-2019-HagelskjaerSKB #constraints #estimation #industrial #performance #precise
- Using spatial constraints for fast set-up of precise pose estimation in an industrial setting (FH, TRS, NK, AGB), pp. 1308–1314.
- CASE-2019-HekmatnejadPF #scheduling #smt
- Task Scheduling with Nonlinear Costs using SMT Solvers (MH, GP, GF), pp. 183–188.
- CASE-2019-HoangPDZH #configuration management #multi
- Reconfigurable Multi-UAV Formation Using Angle-Encoded PSO (VTH, MDP, THD, QZ, QPH), pp. 1670–1675.
- CASE-2019-HongCL #learning #locality #mobile #realtime
- Real-time Visual-Based Localization for Mobile Robot Using Structured-View Deep Learning (YFH, YMC, CHGL), pp. 1353–1358.
- CASE-2019-HuML #petri net
- Active Diagnosis of Petri Nets Using Q-Diagnoser (YH, ZM, ZL), pp. 203–208.
- CASE-2019-ImamM #metric #modelling
- Thermal Modeling of Indoor Spaces using Illumination Measurement as a Surrogate for Solar Heat Gain (MHTI, SM), pp. 1093–1098.
- CASE-2019-JoshiLBB
- Motion-planning Using RRTs for a Swarm of Robots Controlled by Global Inputs (PJ, JL, DB, ATB), pp. 1163–1168.
- CASE-2019-KazmiNVRC #detection #learning #recognition
- Vehicle tire (tyre) detection and text recognition using deep learning (WK, IN, GV, PR, AC), pp. 1074–1079.
- CASE-2019-KumarAS #array #monitoring
- Speed and Separation Monitoring using On-Robot Time-of-Flight Laser-ranging Sensor Arrays (SK, SA, FS), pp. 1684–1691.
- CASE-2019-LaiL #detection #learning
- Video-Based Windshield Rain Detection and Wiper Control Using Holistic-View Deep Learning (CCL, CHGL), pp. 1060–1065.
- CASE-2019-LiGZYWSZ #detection #fault
- Detection model of invisible weld defects using magneto-optical imaging induced by rotating magnetic field (YL, XG, YZ, DY, CW, YS, NZ), pp. 1–5.
- CASE-2019-LiuZHZWW #estimation #learning #network
- sEMG-Based Continuous Estimation of Knee Joint Angle Using Deep Learning with Convolutional Neural Network (GL, LZ, BH, TZ, ZW, PW), pp. 140–145.
- CASE-2019-LuoLLWG #multi #optimisation #problem #scheduling
- Green Job Shop Scheduling Problem with Machine at Different Speeds using a multi-objective grey wolf optimization algorithm* (YL, CL, XL, LW, LG0), pp. 573–578.
- CASE-2019-MackensenKRS #automation #energy #smarttech
- Energy autonomous automation of Smart Home applications using the example of a wireless Indoor Smart Gardening system (EM, JK, AR, AS), pp. 1087–1092.
- CASE-2019-MerktIYV #towards
- Towards Shared Autonomy Applications using Whole-body Control Formulations of Locomanipulation (WM, VI, YY, SV), pp. 1206–1211.
- CASE-2019-NguyenLLGL #network #self
- Visual-Guided Robot Arm Using Self-Supervised Deep Convolutional Neural Networks (VTN, CL, CHGL, SMG, JJJL), pp. 1415–1420.
- CASE-2019-NiuLNLW #detection #fault #generative #named #network
- DefectGAN: Weakly-Supervised Defect Detection using Generative Adversarial Network (SN, HL, TN, BL, XW), pp. 127–132.
- CASE-2019-PangXHP #modelling #multi #optimisation
- optimizing outpatient Department Staffing Level using Multi-Fidelity Models (BP, XX, BH, YP), pp. 715–720.
- CASE-2019-PirehgalinTOV #analysis #automation #image #video #visual notation
- Automatic Visual Leakage Inspection by Using Thermographic Video and Image Analysis (MFP, ET, MO, BVH), pp. 1282–1288.
- CASE-2019-PitschlP #adaptation #maintenance #mobile #persistent #reasoning
- Obstacle Persistent Adaptive Map Maintenance for Autonomous Mobile Robots using Spatio-temporal Reasoning (MLP, MWP), pp. 1023–1028.
- CASE-2019-RobinsonSP #heuristic #visual notation
- Bin-Picking using Model-Free Visual Heuristics and Grasp-Constrained Imaging (CR, MNS, DOP), pp. 1618–1624.
- CASE-2019-RoselliHRFA #equivalence #on the
- On the Use of Equivalence Classes for Optimal and Sub-Optimal Bin Covering (SFR, FH, SR, MF, KÅ), pp. 1004–1009.
- CASE-2019-RoyMN #adaptation #visual notation
- Dynamic Eye-in-Hand Visual Servoing using Adaptive Backstepping with a Supervisory Feature Jacobian (PLGR, CJBM, JN), pp. 1131–1137.
- CASE-2019-SchulerS #analysis #automation #modelling #process #towards
- Spray pattern analysis using wet-mix concrete for model based process control towards automated construction (BS, OS), pp. 661–666.
- CASE-2019-SharabianiBGND #algorithm #kernel #polynomial
- A Computer-Aided System for Determining the Application Range of a Warfarin Clinical Dosing Algorithm Using Support Vector Machines with a Polynomial Kernel Function (AS, AB, WLG, RN, HD), pp. 418–423.
- CASE-2019-SunLY #detection #network
- Railway Joint Detection Using Deep Convolutional Neural Networks (YS, YL, CY), pp. 235–240.
- CASE-2019-ThonnessenSFCK #quickcheck #safety #testing
- Testing Safety PLCs Using QuickCheck (DT, NS, MF, KC, SK), pp. 1–6.
- CASE-2019-WangJRH #image #realtime #scalability
- Real-time control for large scale additive manufacturing using thermal images (FW, FJ, KR, NH), pp. 36–41.
- CASE-2019-WannerS #flexibility #polynomial #programming
- Tool-center-point control of a flexible link concrete pump with hydraulic limitations using quadratic programming (JW, OS), pp. 561–566.
- CASE-2019-WarsewaBRST #design #distributed #scalability
- Decentralized and Distributed Observer Design for Large-Scale Structures using Dynamic Condensation (AW, MB, PR, OS, CT), pp. 1256–1262.
- CASE-2019-XiaoH0HZ #detection #fault
- Surface Defect Detection using Hierarchical Features (LX, TH, BW0, YH, JZ), pp. 1592–1596.
- CASE-2019-ZhangLWGG #fault #learning #network
- Fault Diagnosis Using Unsupervised Transfer Learning Based on Adversarial Network (ZZ, XL, LW, LG0, YG), pp. 305–310.
- CGO-2019-KimK #generative #hardware
- Translating CUDA to OpenCL for Hardware Generation using Neural Machine Translation (YK, HK), pp. 285–286.
- CGO-2019-KruppeOS0 #lightweight
- Extending LLVM for Lightweight SPMD Vectorization: Using SIMD and Vector Instructions Easily from Any Language (RK, JO, LS, AK0), pp. 278–279.
- CGO-2019-SunBSB #graph #reasoning
- Reasoning about the Node.js Event Loop using Async Graphs (HS, DB, FS, WB), pp. 61–72.
CAV-2019-DavisHK #fault #formal method #multi #protocol #proving- When Human Intuition Fails: Using Formal Methods to Find an Error in the “Proof” of a Multi-agent Protocol (JAD, LRH, DBK), pp. 366–375.
- CAV-2019-ElfarWP #game studies #synthesis
- Security-Aware Synthesis Using Delayed-Action Games (ME, YW0, MP), pp. 180–199.
- CAV-2019-LiuWL #source code #verification
- Verifying Asynchronous Event-Driven Programs Using Partial Abstract Transformers (PL, TW, AL), pp. 386–404.
- CAV-2019-LiuZWYLLYZ #algorithm #hoare #logic #quantum #verification
- Formal Verification of Quantum Algorithms Using Quantum Hoare Logic (JL, BZ, SW, SY, TL, YL, MY, NZ), pp. 187–207.
ICST-2019-CoppikSS #fuzzing #memory management #named- MemFuzz: Using Memory Accesses to Guide Fuzzing (NC, OS, NS), pp. 48–58.
- ICST-2019-HellhakeSW #black box #data flow #distributed #integration #test coverage #testing
- Using Data Flow-Based Coverage Criteria for Black-Box Integration Testing of Distributed Software Systems (DH, TS, SW0), pp. 420–429.
- ICST-2019-LeeHYKKY #integration #network #static analysis
- Classifying False Positive Static Checker Alarms in Continuous Integration Using Convolutional Neural Networks (SL, SH, JY, TK, CJK, SY), pp. 391–401.
- ICST-2019-PatersonCAKFM #empirical #fault #predict #testing
- An Empirical Study on the Use of Defect Prediction for Test Case Prioritization (DP, JC, RA, GMK, GF, PM), pp. 346–357.
- ICST-2019-Radavelli #modelling #testing
- Using Testing to Repair Models (MR), pp. 489–491.
ICTSS-2019-BombardaBGRDL #consistency #generative #protocol #refinement #state machine #testing- Combining Model Refinement and Test Generation for Conformance Testing of the IEEE PHD Protocol Using Abstract State Machines (AB, SB, AG, MR, FD, YL), pp. 67–85.
- ICTSS-2019-BozicW #testing
- Testing Chatbots Using Metamorphic Relations (JB, FW), pp. 41–55.
- ICTSS-2019-Huerta-GuevaraA19a #adaptation #named #performance #testing
- DYNAMOJM: A JMeter Tool for Performance Testing Using Dynamic Workload Adaptation (OHG, VAR, LM0, AOPD), pp. 234–241.
TAP-2019-CavalcantiBHL #csp #testing- Testing Robots Using CSP (AC, JB, RMH, RL), pp. 21–38.
VMCAI-2019-AndreFMS #abstraction #algorithm #industrial #model checking #parametricity #verification- Verification of an Industrial Asynchronous Leader Election Algorithm Using Abstractions and Parametric Model Checking (ÉA, LF, JMM, RS), pp. 409–424.
- VMCAI-2019-BallabrigaFGLR #memory management #static analysis
- Static Analysis of Binary Code with Memory Indirections Using Polyhedra (CB, JF, LG, GL, JR), pp. 114–135.
- VMCAI-2019-DeckerP #ltl #model checking #quantifier
- Flat Model Checking for Counting LTL Using Quantifier-Free Presburger Arithmetic (ND, AP), pp. 513–534.
- VMCAI-2019-NguyenTC #automation #program repair #verification
- Automatic Program Repair Using Formal Verification and Expression Templates (TTN, QTT, WNC), pp. 70–91.
ECSA-2018-ChangS #as a service #mobile- Providing Context as a Service Using Service-Oriented Mobile Indie Fog and Opportunistic Computing (CC, SNS), pp. 219–235.
- ECSA-2018-SchneiderBK #information management #quality #trade-off
- Using Informal Knowledge for Improving Software Quality Trade-Off Decisions (YS, AB, AK), pp. 265–283.
ICSA-2018-Yasaweerasinghelage #architecture #data analysis #modelling #performance #predict #privacy #simulation- Predicting the Performance of Privacy-Preserving Data Analytics Using Architecture Modelling and Simulation (RY, MS, IW, HYP), pp. 166–175.
JCDL-2018-AlonsoKT #evolution #how #social- How it Happened: Discovering and Archiving the Evolution of a Story Using Social Signals (OA, VK, SET), pp. 193–202.
- JCDL-2018-KobayashiS0 #distributed #recommendation #representation
- Citation Recommendation Using Distributed Representation of Discourse Facets in Scientific Articles (YK, MS, YM0), pp. 243–251.
- JCDL-2018-MaiGS #learning #performance #semantics
- Using Deep Learning for Title-Based Semantic Subject Indexing to Reach Competitive Performance to Full-Text (FM, LG, AS), pp. 169–178.
- JCDL-2018-PoziMBJK #editing
- Preserving Author Editing History Using Blockchain Technology (MSMP, GM, AAB, AJ, YK), pp. 165–168.
- EDM-2018-BotelhoBOH #detection
- Studying Affect Dynamics and Chronometry Using Sensor-Free Detectors (AFB, RSB, JO, NTH).
- EDM-2018-CookOKD #approach #authentication #education
- An Open Vocabulary Approach for Estimating Teacher Use of Authentic Questions in Classroom Discourse (CC, AO, SK, SD).
- EDM-2018-EstebanGR #algorithm #approach #hybrid #multi #recommendation #search-based #student
- A Hybrid Multi-Criteria approach using a Genetic Algorithm for Recommending Courses to University Students (AE, AZG, CR).
- EDM-2018-HalpernTWGPDG
- Knowledge Tracing Using the Brain (DH, ST, HYW, CG, POP, LD, TMG).
- EDM-2018-HoernleGGPR #interactive #markov #modelling #simulation #student
- Modeling the Effects of Students' Interactions with Immersive Simulations using Markov Switching Systems (NH, YG, BJG, PP, AR).
- EDM-2018-MittalNSDDK #knowledge base #multi
- Using a Common Sense Knowledge Base to Auto Generate Multi-Dimensional Vocabulary Assessments (RSM, SN, MS, UD, PD, RK).
- EDM-2018-NandaHWDG #comprehension #modelling #online #topic
- Understanding Learners' Opinion about Participation Certificates in Online Courses using Topic Modeling (GN, NMH, DRW, KAD, DG).
- EDM-2018-NguyenL #modelling #student
- Using Student Logs to Build Bayesian Models of Student Knowledge and Skills (HN, CWL).
- EDM-2018-ReillyRS #collaboration #learning #multi
- Exploring Collaboration Using Motion Sensors and Multi-Modal Learning Analytics (JMR, MR, BS).
- EDM-2018-SalesBPH #big data #testing
- Using Big Data to Sharpen Design-Based Inference in A/B Tests (AS, AB, TP, NTH).
- ICPC-2018-OttAHBAFL #learning #network #programming language
- Learning lexical features of programming languages from imagery using convolutional neural networks (JO, AA, PH, NB, HA, CF, EL), pp. 336–339.
- ICPC-2018-TakahashiSHS #case study #debugging #locality #smell
- A preliminary study on using code smells to improve bug localization (AT, NSL, SH, MS), pp. 324–327.
- ICSME-2018-Alsolai #maintenance #object-oriented #predict
- Predicting Software Maintainability in Object-Oriented Systems Using Ensemble Techniques (HA), pp. 716–721.
- ICSME-2018-FrickG0P #difference #generative
- Generating Accurate and Compact Edit Scripts Using Tree Differencing (VF, TG, FB0, MP0), pp. 264–274.
- ICSME-2018-IshioMSI #detection #distance #normalisation
- Cloned Buggy Code Detection in Practice Using Normalized Compression Distance (TI, NM, KS, KI), pp. 591–594.
- ICSME-2018-PalombaZL #automation #detection #information retrieval #smell
- Automatic Test Smell Detection Using Information Retrieval Techniques (FP, AZ, ADL), pp. 311–322.
- ICSME-2018-RahmanR #code search #crowdsourcing #data analysis #effectiveness #query
- Effective Reformulation of Query for Code Search Using Crowdsourced Knowledge and Extra-Large Data Analytics (MMR0, CKR), pp. 473–484.
- ICSME-2018-RahmanR18a #api #code search #crowdsourcing #data analysis #named #query
- NLP2API: Query Reformulation for Code Search Using Crowdsourced Knowledge and Extra-Large Data Analytics (MMR0, CKR), p. 714.
- ICSME-2018-SchlieSS #analysis #matlab #matrix #modelling #multi
- Comparing Multiple MATLAB/Simulink Models Using Static Connectivity Matrix Analysis (AS, SS, IS), pp. 160–171.
- MSR-2018-AfzalG #case study #debugging #ide
- A study on the use of IDE features for debugging (AA, CLG), pp. 114–117.
- MSR-2018-CiborowskaKD #behaviour #detection #developer #reuse #web
- Detecting and characterizing developer behavior following opportunistic reuse of code snippets from the web (AC, NAK, KD), pp. 94–97.
- MSR-2018-LamotheS08 #android #api #automation #case study #experience #migration
- Exploring the use of automated API migrating techniques in practice: an experience report on Android (ML, WS), pp. 503–514.
- MSR-2018-MoslehiAR #feature model
- Feature location using crowd-based screencasts (PM, BA, JR), pp. 192–202.
- MSR-2018-RabbaniHSGM #fault #ide #interactive #replication #visual notation
- Revisiting “programmers' build errors” in the visual studio context: a replication study using IDE interaction traces (NR, MSH, SS, KG, SM), pp. 98–101.
- MSR-2018-WilkieHKLNRPK #developer #ide #identification
- Who's this?: developer identification using IDE event data (JW, ZAH, AK, JL, GN, CR, MP, JK), pp. 90–93.
- SANER-2018-KatzRS #decompiler #network
- Using recurrent neural networks for decompilation (DSK, JR, ES), pp. 346–356.
- SANER-2018-LeemansAB18a #analysis #mining #process #scalability #statechart
- The Statechart Workbench: Enabling scalable software event log analysis using process mining (ML, WMPvdA, MGJvdB), pp. 502–506.
- SANER-2018-NucciPTSL #detection #machine learning #question #smell
- Detecting code smells using machine learning techniques: Are we there yet? (DDN, FP, DAT, AS, ADL), pp. 612–621.
- SANER-2018-SantosCPHA #detection #fault #modelling #syntax
- Syntax and sensibility: Using language models to detect and correct syntax errors (EAS, JCC, DP, AH, JNA), pp. 311–322.
- SANER-2018-SotoG #debugging #predict #probability
- Using a probabilistic model to predict bug fixes (MS, CLG), pp. 221–231.
- SCAM-2018-IslamIMRRS #detection #research #transitive
- [Research Paper] Detecting Evolutionary Coupling Using Transitive Association Rules (MAI, MMI, MM, BR, CKR, KAS), pp. 113–122.
- SCAM-2018-JiangCZPP0 #code search #research #semantics
- [Research Paper] Semantics-Based Code Search Using Input/Output Examples (RJ, ZC, ZZ, YP0, MP, TZ0), pp. 92–102.
- SCAM-2018-MostaeenSRRS #automation #design #machine learning #research #tool support #towards #validation
- [Research Paper] On the Use of Machine Learning Techniques Towards the Design of Cloud Based Automatic Code Clone Validation Tools (GM, JS, BR, CKR, KAS), pp. 155–164.
- SCAM-2018-MuylaertR #commit #research #slicing
- [Research Paper] Untangling Composite Commits Using Program Slicing (WM, CDR), pp. 193–202.
- SCAM-2018-NafiRRS #api #detection #documentation #research #similarity
- [Research Paper] CroLSim: Cross Language Software Similarity Detector Using API Documentation (KWN, BR, CKR, KAS), pp. 139–148.
- SCAM-2018-PaceTG #architecture #predict #research #smell #towards
- [Research Paper] Towards Anticipation of Architectural Smells Using Link Prediction Techniques (JADP, AT, DG), pp. 62–71.
CIAA-2018-NozakiHYS #automaton #finite- Enumeration of Cryptarithms Using Deterministic Finite Automata (YN, DH, RY, AS), pp. 286–298.
- FM-2018-0001BFLMR #automaton #energy #nondeterminism #robust #synthesis
- Optimal and Robust Controller Synthesis - Using Energy Timed Automata with Uncertainty (GB0, PB, UF, KGL, NM, PAR), pp. 203–221.
- FM-2018-AkazakiLYDH #cyber-physical #learning
- Falsification of Cyber-Physical Systems Using Deep Reinforcement Learning (TA, SL, YY, YD, JH), pp. 456–465.
- FM-2018-Boralv #automation #design #proving
- Interlocking Design Automation Using Prover Trident (AB), pp. 653–656.
- FM-2018-GeislerH #development #distributed #model checking
- Stepwise Development and Model Checking of a Distributed Interlocking System - Using RAISE (SG, AEH), pp. 277–293.
- IFM-2018-DoughertyGR #analysis #protocol #security #smt
- Security Protocol Analysis in Context: Computing Minimal Executions Using SMT and CPSA (DJD, JDG, JDR), pp. 130–150.
- IFM-2018-GlabbeekHW
- Analysing AWN-Specifications Using mCRL2 (Extended Abstract) (RJvG, PH, DvdW), pp. 398–418.
- IFM-2018-KangMH #constraints #probability #verification
- Probabilistic Verification of Timing Constraints in Automotive Systems Using UPPAAL-SMC (EYK0, DM, LH), pp. 236–254.
- IFM-2018-KornerLM #model checking #state of the art
- State-of-the-Art Model Checking for B and Event-B Using ProB and LTSmin (PK, ML, JM), pp. 275–295.
- IFM-2018-SchmidtKL #formal method #generative #modelling #synthesis
- Repair and Generation of Formal Models Using Synthesis (JS, SK, ML), pp. 346–366.
- SEFM-2018-BabaeeGF #framework #learning #predict #runtime #statistics #verification
- Prevent : A Predictive Run-Time Verification Framework Using Statistical Learning (RB, AG, SF), pp. 205–220.
- SEFM-2018-DinSC #exception #verification
- Program Verification for Exception Handling on Active Objects Using Futures (CCD, RS, TCC), pp. 73–88.
- SEFM-2018-DuboisGPC #interactive #protocol #proving #theorem proving
- Exploring Properties of a Telecommunication Protocol with Message Delay Using Interactive Theorem Prover (CD, OG, JP, MC), pp. 239–253.
- SEFM-2018-GolraDSSG #requirements #specification
- Bridging the Gap Between Informal Requirements and Formal Specifications Using Model Federation (FRG, FD, JS, IS, SG), pp. 54–69.
- ICFP-2018-AlmeidaCM0P #assessment #automation #case study #education #experience #functional #game studies #how
- Teaching how to program using automated assessment and functional glossy games (experience report) (JBA, AC, NM, HP0, JP), p. 17.
- ICFP-2018-StampoulisC #functional #higher-order #learning #logic programming #prolog #prototype
- Prototyping a functional language using higher-order logic programming: a functional pearl on learning the ways of λProlog/Makam (AS, AC), p. 30.
- AIIDE-2018-MathewsonM #game studies #named
- Improbotics: Exploring the Imitation Game Using Machine Intelligence in Improvised Theatre (KWM, PM), pp. 59–66.
- CHI-PLAY-2018-ByrneMM #case study #experience #game studies
- AR Fighter: Using HMDs to create Vertigo Play Experiences (RB, JM, F'M), pp. 45–57.
- CHI-PLAY-2018-FrommelFR0 #self
- Emotion-based Dynamic Difficulty Adjustment Using Parameterized Difficulty and Self-Reports of Emotion (JF, FF, KR, MW0), pp. 163–171.
- CHI-PLAY-2018-VellaPKPMJ #case study #game studies
- Using Applied Games to Engage mHealth Users: A Case Study of MindMax (KV, NP, MK, BP, JM, DJ0), pp. 511–522.
- CIG-2018-GlavinM #experience #learning
- Skilled Experience Catalogue: A Skill-Balancing Mechanism for Non-Player Characters using Reinforcement Learning (FGG, MGM), pp. 1–8.
- CIG-2018-Guerrero-Romero #algorithm #design #game studies #testing
- Using a Team of General AI Algorithms to Assist Game Design and Testing (CGR, SML, DPL), pp. 1–8.
- CIG-2018-KaravolosLY #automation #design
- Using a Surrogate Model of Gameplay for Automated Level Design (DK, AL, GNY), pp. 1–8.
- CIG-2018-KosmidesDAKOL #game studies #named
- InLife: Combining Real Life with Serious Games using IoT (PK, KPD, EFA, NK, YO, VDL), pp. 1–7.
- CIG-2018-StreckW #animation #markov
- Using Discrete Time Markov Chains for Control of Idle Character Animation (AS, TW), pp. 1–4.
- CIG-2018-TziortziotiMMVC #education #game studies #internet #process
- Scenarios for Educational and Game Activities using Internet of Things Data (CT, IM, GM, AV, IC), pp. 1–8.
- FDG-2018-PlumbKS #clustering #game studies #hybrid #multi #network #online
- Hybrid network clusters using common gameplay for massively multiplayer online games (JNP, SKK, RS), p. 10.
- FDG-2018-SiljebratAP #towards
- Towards human-like artificial intelligence using StarCraft 2 (HS, CA, AP), p. 4.
- FDG-2018-SmithPV #generative #graph #programming #set
- Graph-based generation of action-adventure dungeon levels using answer set programming (TS0, JAP, AV), p. 10.
- VS-Games-2018-BardisKSVD #evolution #image
- Image Warping Using WebGL for a Smart Avatar Animating Body Weight Evolution (GB, YK, NS, AV, ND), pp. 1–4.
- VS-Games-2018-LewisAMCKBDM #game studies #mobile
- Balance Trucks: Using Crowd-Sourced Data to Procedurally-Generate Gameplay within Mobile Games (MRL, SA, LM, SC, LCK, AB, SD, AM), pp. 1–4.
- VS-Games-2018-Lim #case study #protocol
- Using Think-Aloud Protocol in Looking at the Framing of One's Character with a Case Study on Terraria (JSL), pp. 1–4.
- VS-Games-2018-MunozVCMH #artificial reality #coordination #diagrams
- Dynamic Systems Theory in Human Movement Exploring Coordination Patterns by Angle-Angle Diagrams Using Kinect (JEMC, JFV, SC, MFM, ÓAH), pp. 1–4.
- VS-Games-2018-OberdorferL #game studies
- Effectivity of Affine Transformation Knowledge Training Using Game Mechanics (SO, MEL), pp. 1–8.
- VS-Games-2018-OberdorferL18a #encoding #game studies
- Gamified Knowledge Encoding: Knowledge Training Using Game Mechanics (SO, MEL), pp. 1–2.
- VS-Games-2018-OberdorferL18b #effectiveness #game studies
- Effective Orbital Mechanics Knowledge Training Using Game Mechanics (SO, MEL), pp. 1–8.
- VS-Games-2018-OhmotoTN #comprehension
- Improving Context Understanding Using Avatar's Affective Expressions Reflecting Operator's Mental States (YO, ST, TN), pp. 1–4.
- VS-Games-2018-RallisLGVDD #analysis #artificial reality #game studies #learning #visualisation
- An Embodied Learning Game Using Kinect and Labanotation for Analysis and Visualization of Dance Kinesiology (IR, AL, IG, AV, ND, AD), pp. 1–8.
- VS-Games-2018-Ramic-Brkic #education #game studies
- Enhancing Progressive Education through the Use of Serious Games (BRB), pp. 1–4.
- VS-Games-2018-WuGHL #3d #data fusion #multi #robust #towards
- Towards Robust 3D Skeleton Tracking Using Data Fusion from Multiple Depth Sensors (YW, LG, SH, RWL), pp. 1–4.
- CIKM-2018-AdigaCKMRRS #modelling #network #probability #query
- Inferring Probabilistic Contagion Models Over Networks Using Active Queries (AA, VCM, CJK, MVM, SSR, DJR, RES), pp. 377–386.
- CIKM-2018-ANR #algorithm #generative #higher-order #scalability
- A Scalable Algorithm for Higher-order Features Generation using MinHash (PA, NN, RR), pp. 1213–1222.
- CIKM-2018-CirsteaMMG0 #correlation #multi #network
- Correlated Time Series Forecasting using Multi-Task Deep Neural Networks (RGC, DVM, GMM, CG, BY0), pp. 1527–1530.
- CIKM-2018-DeutchGM #detection #privacy
- Preserving Privacy of Fraud Detection Rule Sharing Using Intel's SGX (DD, YG, TM), pp. 1935–1938.
- CIKM-2018-GeDJNW #personalisation
- Personalizing Search Results Using Hierarchical RNN with Query-aware Attention (SG, ZD, ZJ, JYN, JRW), pp. 347–356.
- CIKM-2018-GeZZCLYHLSLYHZZ #behaviour #image #matter #modelling #visual notation
- Image Matters: Visually Modeling User Behaviors Using Advanced Model Server (TG, LZ, GZ, KC, SL, HY, ZH, BL, PS, HL, PY, SH, ZZ, XZ, YZ, KG), pp. 2087–2095.
- CIKM-2018-HashemiWKZC #query #user satisfaction
- Measuring User Satisfaction on Smart Speaker Intelligent Assistants Using Intent Sensitive Query Embeddings (SHH, KW, AEK, IZ, PAC), pp. 1183–1192.
- CIKM-2018-Kieu0GJ
- Distinguishing Trajectories from Different Drivers using Incompletely Labeled Trajectories (TK, BY0, CG, CSJ), pp. 863–872.
- CIKM-2018-KweeCPL #lifecycle #mining #named #visualisation
- Traffic-Cascade: Mining and Visualizing Lifecycles of Traffic Congestion Events Using Public Bus Trajectories (ATK, MFC, PKP, EPL), pp. 1955–1958.
- CIKM-2018-LinmansVK #detection #robust #scalability #semantics #web
- Improved and Robust Controversy Detection in General Web Pages Using Semantic Approaches under Large Scale Conditions (JL, BvdV, EK), pp. 1647–1650.
- CIKM-2018-PandeyKS #learning #recommendation
- Recommending Serendipitous Items using Transfer Learning (GP0, DK, AS), pp. 1771–1774.
- CIKM-2018-PatidarAVS #automation #modelling
- Automatic Conversational Helpdesk Solution using Seq2Seq and Slot-filling Models (MP, PA, LV, GMS), pp. 1967–1975.
- CIKM-2018-PrasojoKN #fine-grained #information management #named #semantics
- StuffIE: Semantic Tagging of Unlabeled Facets Using Fine-Grained Information Extraction (REP, MK, WN), pp. 467–476.
- CIKM-2018-RoleMN #algorithm #clustering #evaluation #word
- Unsupervised Evaluation of Text Co-clustering Algorithms Using Neural Word Embeddings (FR, SM, MN), pp. 1827–1830.
- CIKM-2018-RoyGBBM #how #information retrieval #normalisation #performance #word
- Using Word Embeddings for Information Retrieval: How Collection and Term Normalization Choices Affect Performance (DR, DG, SB, SB, MM), pp. 1835–1838.
- CIKM-2018-ShangSSLGKLY0
- Investigating Rumor News Using Agreement-Aware Search (JS, JS, TS, XL, AG, FK, ÁDL, CY0, JH0), pp. 2117–2125.
- CIKM-2018-ShenYZPZ #parallel
- Parallel Hashing Using Representative Points in Hyperoctants (CS, MY, CZ, YP, GZ), pp. 813–822.
- CIKM-2018-SyedRN #named #rdf #validation
- FactCheck: Validating RDF Triples Using Textual Evidence (ZHS, MR, ACNN), pp. 1599–1602.
- CIKM-2018-Voorhees #on the #reuse
- On Building Fair and Reusable Test Collections using Bandit Techniques (EMV), pp. 407–416.
- CIKM-2018-ZhangNCC #database #parallel #probability #scalability
- Scalable Entity Resolution Using Probabilistic Signatures on Parallel Databases (YZ, KSN, TC, PC), pp. 2213–2221.
- ECIR-2018-BalikasLRA #distance #documentation #retrieval
- Cross-Lingual Document Retrieval Using Regularized Wasserstein Distance (GB, CL, IR, MRA), pp. 398–410.
- ECIR-2018-DeySK #detection #topic #twitter
- Topical Stance Detection for Twitter: A Two-Phase LSTM Model Using Attention (KD, RS, SK), pp. 529–536.
- ECIR-2018-Jalan0V #classification #learning
- Medical Forum Question Classification Using Deep Learning (RSJ, MG0, VV), pp. 45–58.
- ECIR-2018-McDonaldMO18a #overview #predict #towards
- Towards Maximising Openness in Digital Sensitivity Review Using Reviewing Time Predictions (GM, CM, IO), pp. 699–706.
- ECIR-2018-SinghM #recommendation #symmetry
- Benefits of Using Symmetric Loss in Recommender Systems (GS, SM), pp. 345–356.
- ECIR-2018-Zhang0LZ #analysis #matrix #representation #sentiment #twitter
- Unsupervised Sentiment Analysis of Twitter Posts Using Density Matrix Representation (YZ, DS0, XL, PZ0), pp. 316–329.
- ICML-2018-0001JCCJ #robust
- Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training (XW0, UJ, JC, LC, SJ), pp. 5330–5338.
- ICML-2018-AghazadehSLDSB #feature model #named #scalability #sketching
- MISSION: Ultra Large-Scale Feature Selection using Count-Sketches (AA, RS, DL, GD, AS, RGB), pp. 80–88.
- ICML-2018-ArenzZN #performance #policy
- Efficient Gradient-Free Variational Inference using Policy Search (OA, MZ, GN), pp. 234–243.
- ICML-2018-BajajGHHL #clustering #named
- SMAC: Simultaneous Mapping and Clustering Using Spectral Decompositions (CB, TG, ZH, QH, ZL), pp. 334–343.
- ICML-2018-BangS #generative #network
- Improved Training of Generative Adversarial Networks using Representative Features (DB, HS), pp. 442–451.
- ICML-2018-BansalAB #agile #design
- Using Inherent Structures to design Lean 2-layer RBMs (AB, AA, CB), pp. 452–460.
- ICML-2018-BarretoBQSSHMZM #learning #policy
- Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement (AB, DB, JQ, TS, DS, MH, DJM, AZ, RM), pp. 510–519.
- ICML-2018-ChenLW #learning #scalability
- Scalable Bilinear Learning Using State and Action Features (YC, LL0, MW), pp. 833–842.
- ICML-2018-DaiZGW #network
- Compressing Neural Networks using the Variational Information Bottleneck (BD, CZ, BG, DPW), pp. 1143–1152.
- ICML-2018-DharGE #generative #modelling
- Modeling Sparse Deviations for Compressed Sensing using Generative Models (MD, AG, SE), pp. 1222–1231.
- ICML-2018-FengWCS #learning #multi #network #parametricity
- Nonparametric variable importance using an augmented neural network with multi-task learning (JF, BDW, MC, NS), pp. 1495–1504.
- ICML-2018-GaninKBEV #image #learning #source code
- Synthesizing Programs for Images using Reinforced Adversarial Learning (YG, TK, IB, SMAE, OV), pp. 1652–1661.
- ICML-2018-HuangA0S #learning
- Learning Deep ResNet Blocks Sequentially using Boosting Theory (FH, JTA, JL0, RES), pp. 2063–2072.
- ICML-2018-HuWL #analysis #probability #reduction #source code
- Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs (BH, SW, LL), pp. 2043–2052.
- ICML-2018-IcarteKVM #composition #learning #specification
- Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning (RTI, TQK, RAV, SAM), pp. 2112–2121.
- ICML-2018-JohnH #fourier #process #scalability
- Large-Scale Cox Process Inference using Variational Fourier Features (STJ, JH), pp. 2367–2375.
- ICML-2018-KaiserBRVPUS #modelling #performance #sequence
- Fast Decoding in Sequence Models Using Discrete Latent Variables (LK, SB, AR, AV, NP, JU, NS), pp. 2395–2404.
- ICML-2018-KalimerisSSW #learning
- Learning Diffusion using Hyperparameters (DK, YS, KS, UW), pp. 2425–2433.
- ICML-2018-KeivaniS #nearest neighbour
- Improved nearest neighbor search using auxiliary information and priority functions (OK, KS), pp. 2578–2586.
- ICML-2018-KuleshovFE #learning #nondeterminism
- Accurate Uncertainties for Deep Learning Using Calibrated Regression (VK, NF, SE), pp. 2801–2809.
- ICML-2018-RaileanuDSF #learning #modelling #multi
- Modeling Others using Oneself in Multi-Agent Reinforcement Learning (RR, ED, AS, RF), pp. 4254–4263.
- ICML-2018-SharmaNK #clique #problem #random
- Solving Partial Assignment Problems using Random Clique Complexes (CS, DN, MK), pp. 4593–4602.
- ICML-2018-Sinha #clustering #matrix #random
- K-means clustering using random matrix sparsification (KS), pp. 4691–4699.
- ICML-2018-WeissGY #automaton #network #query
- Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples (GW, YG, EY), pp. 5244–5253.
- ICML-2018-YoonJS #generative #named
- GAIN: Missing Data Imputation using Generative Adversarial Nets (JY, JJ, MvdS), pp. 5675–5684.
- ICML-2018-YoonJS18a #dataset #generative #modelling #multi #named #network #predict
- RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks (JY, JJ, MvdS), pp. 5685–5693.
ICPR-2018-AbdeldayemB #automation #detection- Automatically Detecting Arrhythmia-related Irregular Patterns using the Temporal and Spectro-Temporal Textures of ECG Signals (SSA, TB), pp. 2301–2307.
- ICPR-2018-AfonsoPSP #classification #learning
- Improving Optimum- Path Forest Classification Using Unsupervised Manifold Learning (LCSA, DCGP, ANdS, JPP), pp. 560–565.
- ICPR-2018-AkdemirBS #locality #realtime
- Real-time Vehicle Localization and Tracking Using Monocular Panomorph Panoramic Vision (BA, ANB, LMS), pp. 2350–2355.
- ICPR-2018-AzzopardiFGSV #gender #image #recognition
- Gender recognition from face images using trainable shape and color features (GA, PF, AG, AS, MV), pp. 1983–1988.
- ICPR-2018-BeheraDDR #recognition
- Air Signature Recognition Using Deep Convolutional Neural Network-Based Sequential Model (SKB, AKD, DPD, PPR0), pp. 3525–3530.
- ICPR-2018-BhuniaBBKB0P #network
- Handwriting Trajectory Recovery using End-to-End Deep Encoder-Decoder Network (AKB, AB, AKB, AK, PB, PPR0, UP0), pp. 3639–3644.
- ICPR-2018-BhuniaBBKB0P18a #generative #image #network #word
- Word Level Font-to-Font Image Translation using Convolutional Recurrent Generative Adversarial Networks (AKB, AKB, PB, AK, AB, PPR0, UP0), pp. 3645–3650.
- ICPR-2018-BicegoLDGA #mining #modelling #topic
- Mining NMR Spectroscopy Using Topic Models (MB, PL, MD, FG, MA), pp. 3784–3789.
- ICPR-2018-CombinidoMA #approach #image #network
- A Convolutional Neural Network Approach for Estimating Tropical Cyclone Intensity Using Satellite-based Infrared Images (JSC, JRM, JA), pp. 1474–1480.
- ICPR-2018-CuiZZH #learning #multi #network #recognition
- Multi-source Learning for Skeleton -based Action Recognition Using Deep LSTM Networks (RC, AZ, SZ, GH0), pp. 547–552.
- ICPR-2018-CzovnyBSC #3d
- Minutia Matching using 3D Pore Clouds (RKC, ORPB, LS, HSGC), pp. 3138–3143.
- ICPR-2018-DehzangiBI #detection #multi #process
- Activity Detection using Fusion of Multi-Pressure Sensors in Insoles (OD, BAB, OI), pp. 3315–3321.
- ICPR-2018-DehzangiM #behaviour #predict
- Unobtrusive Driver Drowsiness Prediction Using Driving Behavior from Vehicular Sensors (OD, SM), pp. 3598–3603.
- ICPR-2018-DehzangiS #analysis #process #recognition #reduction #robust
- IMU-Based Robust Human Activity Recognition using Feature Analysis, Extraction, and Reduction (OD, VS), pp. 1402–1407.
- ICPR-2018-DehzangiT #detection #network #representation
- Driver Distraction Detection using MEL Cepstrum Representation of Galvanic Skin Responses and Convolutional Neural Networks (OD, MT), pp. 1481–1486.
- ICPR-2018-Dey0GVLP #image #learning #multi #retrieval #sketching
- Learning Cross-Modal Deep Embeddings for Multi-Object Image Retrieval using Text and Sketch (SD, AD0, SKG, EV, JL0, UP0), pp. 916–921.
- ICPR-2018-DongTC #automation #image
- Automatic Inspection of Aerospace Welds Using X-Ray Images (XD, CJT, TFC), pp. 2002–2007.
- ICPR-2018-DuanMKY #classification #image
- A New Single Image Super-resolution Method Using SIMK-based Classification and ISRM Technique (PD, AM, XK, CY), pp. 3043–3048.
- ICPR-2018-El-GamalEAGBHKE #framework
- Significant Region-Based Framework for Early Diagnosis of Alzheimer's Disease Using 11C PiB-PET Scans (FEZAEG, MME, AA, MG, GNB, HH, RK, ASEB), pp. 2989–2994.
- ICPR-2018-EskenaziGO #component #image
- Watercolor, Segmenting Images Using Connected Color Components (SE, PGK, JMO), pp. 3633–3638.
- ICPR-2018-GarciaLSH #classification #complexity #metric #recommendation
- Classifier Recommendation Using Data Complexity Measures (LPFG, ACL, MCPdS, TKH), pp. 874–879.
- ICPR-2018-GarrettR #3d #network #performance
- Fast Descriptor Extraction for Contextless 3D Registration Using a Fully Convolutional Network (TG, RR), pp. 1211–1216.
- ICPR-2018-HeYLXLHS #estimation #physics
- Variational Mode Decomposition-Based Heart Rate Estimation Using Wrist-Type Photoplethysmography During Physical Exercise (WH, YY, YL, HX, LL0, WH, MS), pp. 3766–3771.
- ICPR-2018-HibrajVSP #clustering #set
- Speaker Clustering Using Dominant Sets (FH, SV, TS, MP), pp. 3549–3554.
- ICPR-2018-JaberiPF #clustering #probability
- Probabilistic Sparse Subspace Clustering Using Delayed Association (MJ, MP, HF), pp. 2087–2092.
- ICPR-2018-JiQYKZ #automation #image #network #segmentation
- Automatic Prostate Segmentation on MR Images Using Enhanced Holistically-Nested Networks (DJ, JQ, JY, TK, SZ), pp. 3820–3825.
- ICPR-2018-JohnKGKM #estimation
- Free Space, Visible and Missing Lane Marker Estimation using the PsiNet and Extra Trees Regression (VJ, NMK, CG, KK, SM), pp. 189–194.
- ICPR-2018-JyotiD #automation #estimation #geometry #network
- Automatic Eye Gaze Estimation using Geometric & Texture-based Networks (SJ, AD), pp. 2474–2479.
- ICPR-2018-KateFG #visual notation
- Visual Tracking with Breeding Fireflies using Brightness from Background-Foreground Information (PK, MF, PG), pp. 2570–2575.
- ICPR-2018-KawanishiMXTY #estimation
- Which Content in a Booklet is he/she Reading? Reading Content Estimation using an Indoor Surveillance Camera (YK, HM, JX, KT, HY), pp. 1731–1736.
- ICPR-2018-KilKC
- Scene text rectification using glyph and character alignment properties (THK, HIK, NIC), pp. 3663–3668.
- ICPR-2018-KimuraSDNKBI #3d #representation
- Representing a Partially Observed Non-Rigid 3D Human Using Eigen-Texture and Eigen-Deformation (RK, AS, FLD, YN, HK, AB, KI), pp. 1043–1048.
- ICPR-2018-KokakiTKHO #modelling
- Sequential Fish Catch Forecasting Using Bayesian State Space Models (YK, NT, TK, KH, TO), pp. 776–781.
- ICPR-2018-KonwerBBBB0P #generative #network
- Staff line Removal using Generative Adversarial Networks (AK, AKB, AB, AKB, PB, PPR0, UP0), pp. 1103–1108.
- ICPR-2018-KurzendorferBSB #analysis #classification #random #segmentation
- Myocardial Scar Segmentation in LGE-MRI using Fractal Analysis and Random Forest Classification (TK, KB, SS, AB, CF, AKM), pp. 3168–3173.
- ICPR-2018-LeeLC
- Cancelable Biometrics Using Noise Embedding (DHL, SHL, NIC), pp. 3390–3395.
- ICPR-2018-LiangYLH #classification
- A Segmented Local Offset Method for Imbalanced Data Classification Using Quasi-Linear Support Vector Machine (PL, XY, WL, JH), pp. 746–751.
- ICPR-2018-LiaoCQ #image #visualisation
- Visualization of Hyperspectral Images Using Moving Least Squares (DL, SC, YQ), pp. 2851–2856.
- ICPR-2018-LiCGJH #gesture #multimodal #recognition
- Multimodal Gesture Recognition Using Densely Connected Convolution and BLSTM (DL, YC, MkG, SJ, CH), pp. 3365–3370.
- ICPR-2018-LiciottiPPFZ #network #segmentation #semantics
- Convolutional Networks for Semantic Heads Segmentation using Top-View Depth Data in Crowded Environment (DL, MP, RP, EF, PZ), pp. 1384–1389.
- ICPR-2018-LiH #algorithm #estimation #performance #robust
- Fast and Robust Pose Estimation Algorithm for Bin Picking Using Point Pair Feature (ML, KH), pp. 1604–1609.
- ICPR-2018-Liu0H #integration
- High-Quality and Memory-Efficient Volumetric Integration of Depth Maps Using Plane Priors (YL, WG0, ZH), pp. 1749–1754.
- ICPR-2018-LiuH0 #online #optimisation
- Online Temporal Calibration of Camera and IMU using Nonlinear Optimization (JL, ZH, WG0), pp. 1761–1766.
- ICPR-2018-LiW18a #detection #semantics #visual notation
- Visual Relationship Detection Using Joint Visual-Semantic Embedding (BL, YW0), pp. 3291–3296.
- ICPR-2018-LiWK18a #framework #image #learning
- Infrared and Visible Image Fusion using a Deep Learning Framework (HL0, XJW, JK), pp. 2705–2710.
- ICPR-2018-LocBO #documentation #image #network #security
- Document Images Watermarking for Security Issue using Fully Convolutional Networks (CVL, JCB, JMO), pp. 1091–1096.
- ICPR-2018-LuoCCTTKH
- Oil Price Forecasting Using Supervised GANs with Continuous Wavelet Transform Features (ZL, JC, XJC, KT, TT, TK, SH), pp. 830–835.
- ICPR-2018-MaH #generative #network
- Perceptual Face Completion using a Local-Global Generative Adversarial Network (RM, HH0), pp. 1670–1675.
- ICPR-2018-MaierSSWSCF #learning #network #precise #towards
- Precision Learning: Towards Use of Known Operators in Neural Networks (AKM, FS, CS, TW, SS, JHC, RF), pp. 183–188.
- ICPR-2018-MaLHY #estimation #hybrid #network
- Image-based Air Pollution Estimation Using Hybrid Convolutional Neural Network (JM, KL, YH, JY), pp. 471–476.
- ICPR-2018-MerchantSKM #dataset #image
- Appearance-based data augmentation for image datasets using contrast preserving sampling (AKM, TQS, BK, RM), pp. 1235–1240.
- ICPR-2018-MohantyDG #detection #performance
- An Efficient System for Hazy Scene Text Detection using a Deep CNN and Patch-NMS (SM, TD, HPG), pp. 2588–2593.
- ICPR-2018-MustaniemiKSMH #detection #metric #performance
- Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements (JM, JK, SS, JM, JH), pp. 3068–3073.
- ICPR-2018-NadeemHS #algorithm #automation #detection #image #segmentation
- An automated airway segmentation algorithm for CT images using topological leakage detection and volume freezing (SAN, EAH, PKS), pp. 1181–1186.
- ICPR-2018-NguyenTL #data-driven #learning
- Are French Really That Different? Recognizing Europeans from Faces Using Data-Driven Learning (VDN, MT, JL), pp. 2729–2734.
- ICPR-2018-PassalisT #information management #network #similarity
- Neural Network Knowledge Transfer using Unsupervised Similarity Matching (NP, AT), pp. 716–721.
- ICPR-2018-PengSCCXJ #architecture #detection #multi
- Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture (DP, ZS, ZC, ZC, LX, LJ), pp. 2528–2533.
- ICPR-2018-PereraAP #generative #multi #named #network
- In2I: Unsupervised Multi-Image-to-Image Translation Using Generative Adversarial Networks (PP, MA, VMP), pp. 140–146.
- ICPR-2018-RhifWF #3d #network #recognition #sequence
- Action Recognition from 3D Skeleton Sequences using Deep Networks on Lie Group Features (MR, HW, IRF), pp. 3427–3432.
- ICPR-2018-RoyT #higher-order #learning
- Learning to Learn Second-Order Back-Propagation for CNNs Using LSTMs (AR, ST), pp. 97–102.
- ICPR-2018-SadafiKHPMS #multi
- Multiple Mice Tracking: Occlusions Disentanglement using a Gaussian Mixture Model (AS, VMK, HH, FP, VM, DS), pp. 2433–2437.
- ICPR-2018-Savchenko #performance #recognition #statistics
- Efficient Statistical Face Recognition Using Trigonometric Series and CNN Features (AVS), pp. 3262–3267.
- ICPR-2018-ShibataIHM #image #set
- Restoration of Sea Surface Temperature Satellite Images Using a Partially Occluded Training Set (SS, MI, AH, MM), pp. 2771–2776.
- ICPR-2018-SuHK #analysis #classification #component #multi #performance
- Efficient Text Classification Using Tree-structured Multi-linear Principal Component Analysis (YS, YH, CCJK), pp. 585–590.
- ICPR-2018-SuJ #analysis #image #multi
- Multi-Spectral Fusion and Denoising of RGB and NIR Images Using Multi-Scale Wavelet Analysis (HS, CJ), pp. 1779–1784.
- ICPR-2018-TayanovKS #classification #learning #predict
- Prediction-based classification using learning on Riemannian manifolds (VT, AK, CYS), pp. 591–596.
- ICPR-2018-UekiHKK #fine-grained #query #retrieval #video
- Fine-grained Video Retrieval using Query Phrases - Waseda_Meisei TRECVID 2017 AVS System - (KU, KH, KK, TK), pp. 3322–3327.
- ICPR-2018-VinayavekhinCMA #comprehension #learning #what
- Focusing on What is Relevant: Time-Series Learning and Understanding using Attention (PV, SC, AM, DJA, GDM, DK, RT), pp. 2624–2629.
- ICPR-2018-WangF #detection
- Saliency Detection using Iterative Dynamic Guided Filtering (CW, YF), pp. 3396–3401.
- ICPR-2018-WangHJ #learning
- Focus on Scene Text Using Deep Reinforcement Learning (HW, SH, LJ), pp. 3759–3765.
- ICPR-2018-WangSH #algorithm #black box #generative
- Universal Perturbation Generation for Black-box Attack Using Evolutionary Algorithms (SW, YS, YH), pp. 1277–1282.
- ICPR-2018-WangZGW #detection #image #multi #network #parametricity
- Fully convolutional neural networks for prostate cancer detection using multi-parametric magnetic resonance images: an initial investigation (YW, BZ, DG, JW), pp. 3814–3819.
- ICPR-2018-WeiCYLL #black box #classification #image
- Explain Black-box Image Classifications Using Superpixel-based Interpretation (YW, MCC, YY, SNL, SL), pp. 1640–1645.
- ICPR-2018-Windeatt #analysis #classification #optimisation
- Optimising Ensemble of Two-Class classifiers using Spectral Analysis (TW), pp. 710–715.
- ICPR-2018-WitmerB #classification #image #learning #multi
- Multi-label Classification of Stem Cell Microscopy Images Using Deep Learning (AW, BB), pp. 1408–1413.
- ICPR-2018-WuW #gesture #recognition
- Applying hand gesture recognition and joint tracking to a TV controller using CNN and Convolutional Pose Machine (YW, CMW), pp. 3086–3091.
- ICPR-2018-WuY0Y #robust
- Robust ECG Biometrics Using Two-Stage Model (BW, GY, LY0, YY), pp. 1062–1067.
- ICPR-2018-XinCCZYW #locality #recognition #visual notation
- Visual Localization in Changing Environments using Place Recognition Techniques (ZX, YC, SC, JZ0, YY, YW), pp. 1785–1790.
- ICPR-2018-XiongJXXLW #documentation #energy #estimation #image
- Historical document image binarization using background estimation and energy minimization (WX0, XJ, JX, ZX, ML, JW), pp. 3716–3721.
- ICPR-2018-XuCG #learning #modelling #multi #random
- Common Random Subgraph Modeling Using Multiple Instance Learning (TX, DKYC, IG), pp. 1205–1210.
- ICPR-2018-XuD #detection #modelling
- Human Routine Change Detection using Bayesian Modelling (YX, DD), pp. 1833–1838.
- ICPR-2018-XuDMB #recognition
- Video-based Emotion Recognition using Aggregated Features and Spatio-temporal Information (JX, YD, LM, HB), pp. 2833–2838.
- ICPR-2018-XuZZ #image #network #recognition
- Screen-rendered text images recognition using a deep residual network based segmentation-free method (XX0, JZ, HZ), pp. 2741–2746.
- ICPR-2018-YamadaIYK #network #segmentation
- Texture Segmentation using Siamese Network and Hierarchical Region Merging (RY, HI, NY, TK), pp. 2735–2740.
- ICPR-2018-Yang0CF #analysis #canonical #correlation #detection #image
- Heterogeneous image change detection using Deep Canonical Correlation Analysis (JY, YZ0, YC, LF), pp. 2917–2922.
- ICPR-2018-YangZT
- Reducing Tongue Shape Dimensionality from Hundreds of Available Resources Using Autoencoder (MY, DZ, JT), pp. 2875–2880.
- ICPR-2018-YanWSLZ #image #learning #network
- Image Captioning using Adversarial Networks and Reinforcement Learning (SY, FW, JSS, WL, BZ), pp. 248–253.
- ICPR-2018-YlimakiHK #3d #re-engineering #refinement
- Accurate 3-D Reconstruction with RGB-D Cameras using Depth Map Fusion and Pose Refinement (MY, JH, JK), pp. 1977–1982.
- ICPR-2018-YuanTLDZ #automation #learning #multi #segmentation
- Fully Automatic Segmentation of the Left Ventricle Using Multi-Scale Fusion Learning (TY, QT, XL, XD, JZ), pp. 3838–3843.
- ICPR-2018-ZhangSOS #identification #network
- Person Re-identification Using Two-Stage Convolutional Neural Network (YZ, JS, DO, HTS), pp. 3341–3346.
- ICPR-2018-ZhanLL #network #recognition #string
- Handwritten Digit String Recognition using Convolutional Neural Network (HZ, SL, YL), pp. 3729–3734.
- ICPR-2018-ZhaoLZTNM #analysis #automation #component #image #multi #robust #segmentation
- Automatic Multi-Atlas Segmentation for Abdominal Images Using Template Construction and Robust Principal Component Analysis (YZ0, HL0, RZ, GT, MN, BHM), pp. 3880–3885.
- ICPR-2018-ZhaoPL0DWQ #learning #locality #semantics #topic
- Learning Topics Using Semantic Locality (ZZ, KP, SL, ZL0, CD, YW, QQ), pp. 3710–3715.
- ICPR-2018-ZhaoSJ #integer #linear #locality #programming
- Temporal Pattern Localization using Mixed Integer Linear Programming (RZ, GS, QJ), pp. 1361–1365.
- ICPR-2018-ZhaoYT #network #order #predict
- Pen Tip Motion Prediction for Handwriting Drawing Order Recovery using Deep Neural Network (BZ, MY, JT), pp. 704–709.
- KDD-2018-DaltayanniDA #automation #segmentation
- Automated Audience Segmentation Using Reputation Signals (MD, AD, LdA), pp. 186–195.
- KDD-2018-DasSCHLCKC #learning #named #performance
- SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression (ND, MS, STC, FH, SL, LC, MEK, DHC), pp. 196–204.
- KDD-2018-GittensRWMGPKRM #data analysis #library #scalability
- Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist (AG, KR, SW, MWM, LG, P, JK, MFR, KJM), pp. 293–301.
- KDD-2018-GohSVH #learning #predict #rule-based
- Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction (GBG, CS, AV, NOH), pp. 302–310.
- KDD-2018-GrbovicC #personalisation #ranking #realtime
- Real-time Personalization using Embeddings for Search Ranking at Airbnb (MG, HC), pp. 311–320.
- KDD-2018-HarelR #network #prototype
- Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks (SH, KR), pp. 331–339.
- KDD-2018-He0LRLTZ #detection
- Detecting Vehicle Illegal Parking Events using Sharing Bikes' Trajectories (TH, JB0, RL, SR, YL, CT, YZ0), pp. 340–349.
- KDD-2018-HundmanCLCS #detection #parametricity
- Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding (KH, VC, CL, IC, TS), pp. 387–395.
- KDD-2018-Janakiraman #learning #multi #safety
- Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning (VMJ), pp. 406–415.
- KDD-2018-JauvionGSGG #optimisation
- Optimization of a SSP's Header Bidding Strategy using Thompson Sampling (GJ, NG, PDS, AG, SG), pp. 425–432.
- KDD-2018-KhuranaASV
- Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN (PK, PA, GMS, LV), pp. 433–442.
- KDD-2018-KumarRBVWKEFMZG #machine learning
- Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks (AK, SAAR, BB, RAV, KHW, CK, SE, AF, AM, JZ, RG), pp. 472–480.
- KDD-2018-LeeRK #classification #graph
- Graph Classification using Structural Attention (JBL, RAR, XK), pp. 1666–1674.
- KDD-2018-OshriHACDWBLE #assessment #framework #learning #quality
- Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning (BO, AH, PA, XC, PD, JW, MB, DBL, SE), pp. 616–625.
- KDD-2018-RouxPMVF #approach #detection #machine learning
- Tax Fraud Detection for Under-Reporting Declarations Using an Unsupervised Machine Learning Approach (DdR, BP, AM, MDPV, CF), pp. 215–222.
- KDD-2018-Ruhrlander0U #modelling #predict
- Improving Box Office Result Predictions for Movies Using Consumer-Centric Models (RPR, MB0, MU), pp. 655–664.
- KDD-2018-ShashikumarSCN #bidirectional #detection #network
- Detection of Paroxysmal Atrial Fibrillation using Attention-based Bidirectional Recurrent Neural Networks (SPS, AJS, GDC, SN), pp. 715–723.
- KDD-2018-Ting #bound #empirical #estimation #fault #named
- Count-Min: Optimal Estimation and Tight Error Bounds using Empirical Error Distributions (DT), pp. 2319–2328.
- KDD-2018-WuCYXXA #clustering #random #scalability
- Scalable Spectral Clustering Using Random Binning Features (LW, PYC, IEHY, FX, YX, CCA), pp. 2506–2515.
- KDD-2018-WuZW #graph #on the
- On Discrimination Discovery and Removal in Ranked Data using Causal Graph (YW, LZ0, XW), pp. 2536–2544.
- KDD-2018-XuLDH #learning #metric #robust
- New Robust Metric Learning Model Using Maximum Correntropy Criterion (JX0, LL, CD, HH), pp. 2555–2564.
- KDD-2018-ZhaoAS0 #classification #dependence #performance #predict
- Prediction-time Efficient Classification Using Feature Computational Dependencies (LZ0, AAF, MS, KZ0), pp. 2787–2796.
ECMFA-2018-RutleIKD #automation #co-evolution #graph transformation #modelling #traceability- Automatic Transformation Co-evolution Using Traceability Models and Graph Transformation (AR, LI, HK, ZD), pp. 80–96.
ICMT-2018-Voelter #design #evolution #functional #kernel- The Design, Evolution, and Use of KernelF — An Extensible and Embeddable Functional Language (MV), pp. 3–55.
- MoDELS-2018-MarussySV #incremental #modelling
- Incremental View Model Synchronization Using Partial Models (KM, OS, DV), pp. 323–333.
- MoDELS-2018-PouraliA #challenge #empirical #modelling #tool support
- An Empirical Investigation to Understand the Difficulties and Challenges of Software Modellers When Using Modelling Tools (PP, JMA), pp. 224–234.
ECOOP-2018-QunaibitBNVF #dynamic typing #optimisation #platform- Accelerating Dynamically-Typed Languages on Heterogeneous Platforms Using Guards Optimization (MQ, SB, YN, SV, MF), p. 29.
- OOPSLA-2018-AlpernasFFRSSW #data flow #information management
- Secure serverless computing using dynamic information flow control (KA, CF, SF, LR, MS, TS, KW), p. 26.
- OOPSLA-2018-WilliamsMW #contract
- The root cause of blame: contracts for intersection and union types (JW, JGM, PW), p. 29.
AdaEurope-2018-JaradatP #contract #design #runtime #safety #verification- Using Safety Contracts to Verify Design Assumptions During Runtime (OJ, SP), pp. 3–18.
LOPSTR-2018-PapapanagiotouF #approach #composition #linear #logic #process #scalability- A Pragmatic, Scalable Approach to Correct-by-Construction Process Composition Using Classical Linear Logic Inference (PP, JDF), pp. 77–93.
- PADL-2018-AnandCN #automation #consistency #detection #logic #nondeterminism
- An Automated Detection of Inconsistencies in SBVR-based Business Rules Using Many-sorted Logic (KA, PKC, RN), pp. 80–96.
- PADL-2018-Crary #code generation #source code
- Hygienic Source-Code Generation Using Functors - (Extended Abstract) (KC), pp. 53–60.
- PLDI-2018-DuckY #c #c++ #detection #effectiveness #fault #memory management #named
- EffectiveSan: type and memory error detection using dynamically typed C/C++ (GJD, RHCY), pp. 181–195.
- PLDI-2018-FengMBD #learning #synthesis
- Program synthesis using conflict-driven learning (YF, RM, OB, ID), pp. 420–435.
- PLDI-2018-HongSKRKPRS #analysis #gpu #kernel #optimisation
- GPU code optimization using abstract kernel emulation and sensitivity analysis (CH, ASR, JK, PSR, SK, LNP, FR, PS), pp. 736–751.
- PLDI-2018-LeeHAN #modelling #probability #search-based #synthesis
- Accelerating search-based program synthesis using learned probabilistic models (WL, KH, RA, MN), pp. 436–449.
- PLDI-2018-RaghothamanKHN #reasoning
- User-guided program reasoning using Bayesian inference (MR, SK, KH, MN), pp. 722–735.
- POPL-2018-Danielsson
- Up-to techniques using sized types (NAD), p. 28.
- POPL-2018-InalaS #named #spreadsheet #web
- WebRelate: integrating web data with spreadsheets using examples (JPI, RS), p. 28.
- POPL-2018-WangDS #abstraction #refinement #synthesis
- Program synthesis using abstraction refinement (XW0, ID, RS), p. 30.
PPDP-2018-NogatzKS #definite clause grammar #prolog #visualisation- Web-based Visualisation for Definite Clause Grammars Using Prolog Meta-Interpreters: System Description (FN, JK, DS), p. 10.
- SAS-2018-RothenbergDH #abstraction #incremental #verification
- Incremental Verification Using Trace Abstraction (BCR, DD, MH), pp. 364–382.
- SAS-2018-Shoham #decidability #distributed #interactive #logic #protocol #verification
- Interactive Verification of Distributed Protocols Using Decidable Logic (SS), pp. 77–85.
- ASE-2018-AbdessalemPNBS #feature model #interactive #testing
- Testing autonomous cars for feature interaction failures using many-objective search (RBA, AP, SN, LCB, TS), pp. 143–154.
- ASE-2018-HabibP #documentation #graph #learning #thread
- Is this class thread-safe? inferring documentation using graph-based learning (AH, MP), pp. 41–52.
- ASE-2018-PatwardhanSSKG #ambiguity #automation #towards
- Towards automating disambiguation of regulations: using the wisdom of crowds (MP, AS, RS, SK, SG), pp. 850–855.
- ASE-2018-QuLCJCHZ #2d #fault #named #network #predict
- node2defect: using network embedding to improve software defect prediction (YQ, TL0, JC, YJ, DC, AH, QZ), pp. 844–849.
- ESEC-FSE-2018-AmarBB0M #difference #finite #modelling
- Using finite-state models for log differencing (HA, LB, NB, DL0, SM), pp. 49–59.
- ESEC-FSE-2018-DashAB #named
- RefiNym: using names to refine types (SKD, MA, ETB), pp. 107–117.
- ESEC-FSE-2018-HuaZWK #approach #automation #generative #lazy evaluation #named #program repair #sketching
- SketchFix: a tool for automated program repair approach using lazy candidate generation (JH, MZ, KW, SK), pp. 888–891.
- ESEC-FSE-2018-HuZY #machine learning #named #reuse #robust #testing #user interface
- AppFlow: using machine learning to synthesize robust, reusable UI tests (GH, LZ, JY), pp. 269–282.
- ESEC-FSE-2018-KimC0 #fault
- Which generated test failures are fault revealing? prioritizing failures based on inferred precondition violations using PAF (MK, SCC, SK0), pp. 679–690.
- ESEC-FSE-2018-LeB0 #mining #named #network #specification
- DSM: a specification mining tool using recurrent neural network based language model (TDBL, LB, DL0), pp. 896–899.
- ESEC-FSE-2018-StoccoYM18a #named #web
- Vista: web test repair using computer vision (AS0, RY, AM0), pp. 876–879.
- ESEC-FSE-2018-TuZZZ #empirical #issue tracking
- Be careful of when: an empirical study on time-related misuse of issue tracking data (FT, JZ, QZ, MZ), pp. 307–318.
- ICSE-2018-AbdessalemNBS #algorithm #testing
- Testing vision-based control systems using learnable evolutionary algorithms (RBA, SN, LCB, TS), pp. 1016–1026.
- ICSE-2018-DamevskiCSKP #behaviour #developer #ide #modelling #predict #topic
- Predicting future developer behavior in the IDE using topic models (KD, HC, DCS, NAK, LLP), p. 932.
- ICSE-2018-HabayebMMB #debugging #markov #on the #predict
- On the use of hidden Markov model to predict the time to fix bugs (MH, SSM, AVM, ABB), p. 700.
- ICSE-2018-KimCK #c #precise #source code #testing
- Precise concolic unit testing of C programs using extended units and symbolic alarm filtering (YK, YC, MK), pp. 315–326.
- ICSE-2018-LangeNTY #behaviour #framework #message passing #verification
- A static verification framework for message passing in Go using behavioural types (JL, NN, BT, NY), pp. 1137–1148.
- ICSE-2018-MechtaevNNGR #implementation #program repair #semantics
- Semantic program repair using a reference implementation (SM, MDN, YN, LG, AR), pp. 129–139.
SLE-2018-MeySHSKFOA #attribute grammar #validation- Continuous model validation using reference attribute grammars (JM, RS, GH, ES, TK0, NF, JÖ, UA), pp. 70–82.
- ASPLOS-2018-DickensGFH #encryption #named #performance
- StrongBox: Confidentiality, Integrity, and Performance using Stream Ciphers for Full Drive Encryption (BDI, HSG, AJF, HH), pp. 708–721.
- CASE-2018-AshouriHNS #approximate #detection #energy #performance
- Energy Performance Based Anomaly Detection in Non-Residential Buildings Using Symbolic Aggregate Approximation (AA, YH, GRN, WS0), pp. 1400–1405.
- CASE-2018-BarretoC #multi #simulation
- Matching the Free-Vibration Response of a Delta Robot with Pick-and-Place Tasks Using Multi-Body Simulation (JPB, BC), pp. 1487–1492.
- CASE-2018-CheonKKKC #design #fuzzy #optimisation
- Systematic Design Method of Controller using Discrete Fuzzy PI Control and Particle Swarm Optimization (JC, JK, HK, SK, YC), pp. 1581–1586.
- CASE-2018-ChuBIICS #learning #multi #online #power management
- Plug-and-Play Power Management Control of All-Electric Vehicles Using Multi-Agent System and On-line Gaussian Learning (KCC, GB, MI, AI, CC, KS), pp. 1599–1604.
- CASE-2018-DasWSP #adaptation #detection #interactive
- Whole Body Human-Robot Collision Detection Using Base-sensor Neuroadaptive Interaction (SKD, IW, MNS, DOP), pp. 278–283.
- CASE-2018-DingLWL #automation #testing
- 6-DOF Automated Flight Testing Using a Humanoid Robot Arm (CD, LL0, CW0, JL), pp. 217–222.
- CASE-2018-FrancoAGABB #approach #deployment #optimisation #probability
- Strategic territorial deployment of hospital pharmacy robots using a stochastic p-robust optimization approach (CF, VA, TG, EAL, MB, HB), pp. 390–395.
- CASE-2018-GaoXDCSG #detection
- Detection of Weld Cracks Using Magneto-optical Imaging (XG, YX, LD, ZC, YS, PPG), pp. 559–564.
- CASE-2018-HaghighiRATMC #detection
- Depth-based Object Detection using Hierarchical Fragment Matching Method (RH, MR, SMA, KPT, AAM0, CMC), pp. 780–785.
- CASE-2018-InuiEMZ #geometry #gpu #process #simulation
- Geometric Simulation of Infeed Grinding Process of Silicon Wafer Using GPU (MI, YE, TM, LZ), pp. 1519–1524.
- CASE-2018-JulienN #coordination #exponential
- Dynamics and Control of Tree-Type Manipulator Systems using Exponential Coordinates (AJ, KN), pp. 136–143.
- CASE-2018-KacarMU #problem #reduction
- Problem Reduction Approaches for Production Planning Using Clearing Functions (NBK, LM, RU), pp. 931–938.
- CASE-2018-KangYJ #analysis #performance #realtime
- Real-time Production Performance Analysis Using Machine Degradation Signals: a Two-Machine Case (YK, HY, FJ), pp. 1501–1506.
- CASE-2018-KuoC #algorithm #capacity #industrial #scheduling #search-based
- Using Auxiliary Capacity Planning Strategy Genetic Algorithm for TFT-LCD photolithography scheduling to empower Industry 3.5 (HAK, CFC0), pp. 920–925.
- CASE-2018-LowO #hybrid #implementation #predict #realtime
- Real-time Implementation of Nonlinear Model Predictive Control for Mechatronic Systems Using a Hybrid Model (SL, DO), pp. 164–167.
- CASE-2018-RibeiroRPS #approach #architecture #design
- An Approach for Architectural Design of Automotive Systems using MARTE and SysML (FGCR, AR, CEP, MSS), pp. 1574–1580.
- CASE-2018-ShimasakiOJTIY #image #pattern matching #pattern recognition #recognition
- HFR-video-based Image Pattern Recognition Using Pixel-level Temporal Frequency Response Matching (KS, TO, MJ, TT, II, KY), pp. 451–456.
- CASE-2018-SpenrathP #heuristic #network #random
- Using Neural Networks for Heuristic Grasp Planning in Random Bin Picking (FS, AP), pp. 258–263.
- CASE-2018-StarkGDBG #integration
- Cloud-based integration of robot engineering data using AutomationML (KS, TG, JD, PB, DG), pp. 645–648.
- CASE-2018-TerzimehicVW #deployment #design
- Using Design Space Exploration to Calculate Deployment Configurations of IEC 61499-based Systems (TT, SV, MW), pp. 881–886.
- CASE-2018-ToriiH #3d #approximate #estimation #parametricity
- Model-less Estimation Method for Robot Grasping Parameters Using 3D Shape Primitive Approximation (TT, MH), pp. 580–585.
- CASE-2018-WijayasingheSPP #adaptation #algorithm #interface #search-based
- Adaptive Interface for Robot Teleoperation using a Genetic Algorithm (IBW, MNS, SP, DOP, SC), pp. 50–56.
- CASE-2018-XuLS0L #realtime #recognition #self
- Real-time Shape Recognition of a Deformable Link by Using Self-Organizing Map (SX, GL, DS, LS0, JL), pp. 586–591.
- CASE-2018-ZhangLFL #integer #linear #programming #sequence
- Shortest Legal Firing Sequence of Net Condition/Event Systems Using Integer Linear Programming (JZ, HL, GF, ZL), pp. 1556–1561.
- CGO-2018-0001LQDL #android #detection #distributed #logic
- Resilient decentralized Android application repackaging detection using logic bombs (QZ0, LL, ZQ, XD, ZL), pp. 50–61.
ESOP-2018-Matsuda0 #combinator #lens #named #programming- HOBiT: Programming Lenses Without Using Lens Combinators (KM, MW0), pp. 31–59.
FASE-2018-Dimovski #model checking- Abstract Family-Based Model Checking Using Modal Featured Transition Systems: Preservation of CTL* (ASD), pp. 301–318.
- FASE-2018-KatirtzisDS #api #clustering
- Summarizing Software API Usage Examples Using Clustering Techniques (NK, TD, CAS), pp. 189–206.
- FASE-2018-LandsbergSK #fault #locality #optimisation #source code #specification
- Optimising Spectrum Based Fault Localisation for Single Fault Programs Using Specifications (DL, YS, DK), pp. 246–263.
- FASE-2018-ParkSR #analysis #framework #web
- EventHandler-Based Analysis Framework for Web Apps Using Dynamically Collected States (JP, KS, SR), pp. 129–145.
- CAV-2018-KongBH #approximate #set
- Reachable Set Over-Approximation for Nonlinear Systems Using Piecewise Barrier Tubes (HK, EB, TAH), pp. 449–467.
- CAV-2018-BouajjaniEMT #abstraction #reasoning #reduction #source code
- Reasoning About TSO Programs Using Reduction and Abstraction (AB, CE, SOM, ST), pp. 336–353.
- CAV-2018-NiemetzPRBT #quantifier
- Solving Quantified Bit-Vectors Using Invertibility Conditions (AN, MP, AR, CWB, CT), pp. 236–255.
- ICST-2018-MahajanAMH #automation #clustering #search-based #similarity #web
- Automated Repair of Internationalization Presentation Failures in Web Pages Using Style Similarity Clustering and Search-Based Techniques (SM, AA, PM, WGJH), pp. 215–226.
- ICST-2018-PradhanW00L #mining #multi #named #testing
- REMAP: Using Rule Mining and Multi-objective Search for Dynamic Test Case Prioritization (DP, SW0, SA0, TY0, ML), pp. 46–57.
- ICST-2018-Rajaram #fault #taxonomy #testing
- Taxonomy Based Testing Using SW91, a Medical Device Software Defect Taxonomy (HKR), pp. 422–423.
IJCAR-2018-KazakovS - Enumerating Justifications Using Resolution (YK, PS), pp. 609–626.
- IJCAR-2018-ZeljicBWR #approximate #float
- Exploring Approximations for Floating-Point Arithmetic Using UppSAT (AZ, PB, CMW, PR), pp. 246–262.
- TAP-2018-HerdaTB #data flow #dependence #graph #testing #verification
- Using Dependence Graphs to Assist Verification and Testing of Information-Flow Properties (MH, SST, BB), pp. 83–102.
- TAP-2018-VorobyovKS #c #case study #detection #experience #runtime #security #verification
- Detection of Security Vulnerabilities in C Code Using Runtime Verification: An Experience Report (KV, NK, JS), pp. 139–156.
- VMCAI-2018-KranzS #analysis #bytecode #composition #on-demand
- Modular Analysis of Executables Using On-Demand Heyting Completion (JK, AS), pp. 291–312.
- ECSA-2017-FilhoRAB #architecture #consistency #design #exception
- Preventing Erosion in Exception Handling Design Using Static-Architecture Conformance Checking (JLMF, LSR, RMCA, RB), pp. 67–83.
- ICSA-2017-GesvindrBG #as a service #design #evaluation #prototype #quality
- Quality Evaluation of PaaS Cloud Application Design Using Generated Prototypes (DG, BB, OG), pp. 31–40.
- ICSA-2017-Yasaweerasinghelage #architecture #latency #modelling #predict #simulation
- Predicting Latency of Blockchain-Based Systems Using Architectural Modelling and Simulation (RY, MS, IW), pp. 253–256.
- JCDL-2017-AlamKWN #re-engineering
- Client-Side Reconstruction of Composite Mementos Using ServiceWorker (SA, MK, MCW, MLN), pp. 237–240.
- JCDL-2017-CastroCWPF #framework #platform #semistructured data
- Classifying Short Unstructured Data Using the Apache Spark Platform (EPSC, SC, EW, DAP, EAF), pp. 129–138.
- JCDL-2017-ChironDCVM #fault #library #towards
- Impact of OCR Errors on the Use of Digital Libraries: Towards a Better Access to Information (GC, AD, MC, MV, JPM), pp. 249–252.
- JCDL-2017-GippBMB #feedback #named #overview
- CryptSubmit: Introducing Securely Timestamped Manuscript Submission and Peer Review Feedback Using the Blockchain (BG, CB, NM, JB), pp. 273–276.
- JCDL-2017-HassanAH #identification #information management
- Identifying Important Citations Using Contextual Information from Full Text (SUH, AA, PH), pp. 41–48.
- JCDL-2017-KleinS
- Discovering Scholarly Orphans Using ORCID (MK, HVdS), pp. 189–198.
- JCDL-2017-KocherS #clustering
- Author Clustering Using SPATIUM (MK, JS), pp. 265–268.
- JCDL-2017-YangHHOZKG #identification #learning #library
- Smart Library: Identifying Books on Library Shelves Using Supervised Deep Learning for Scene Text Reading (XY, DH, WH, AO, ZZ, DK, CLG), pp. 245–248.
CSEET-2017-IacobF #education #requirements- Using Extreme Characters to Teach Requirements Engineering (CI, SF), pp. 107–111.
- CSEET-2017-PintoFSG #open source #perspective
- Training Software Engineers Using Open-Source Software: The Professors' Perspective (GHLP, FFF, IS, MAG), pp. 117–121.
- CSEET-2017-PortelaVOS #case study #experience #industrial #re-engineering
- The Use of Industry Training Strategies in a Software Engineering Course: An Experience Report (CSP, AV, SRBO, MRdAS), pp. 29–36.
- EDM-2017-AndresBSGSC #framework #replication #scalability
- Studying MOOC Completion at Scale Using the MOOC Replication Framework (JMLA, RSB, GS, DG, CAS, SAC).
- EDM-2017-GrawemeyerWSHMP #graph #learning #modelling #student
- Using Graph-based Modelling to explore changes in students' affective states during exploratory learning tasks (BG, AW, SGS, WH, MM, AP).
- EDM-2017-HongB #learning #predict
- A Prediction and Early Alert Model Using Learning Management System Data and Grounded in Learning Science Theory (WJH, MLB).
- EDM-2017-LiuL #student
- Exploring the Relationship Between Student Pre-knowledge and Engagement in MOOC Class Using Polytomous IRT (JL, HL).
- EDM-2017-MadaioLCO #mining #predict
- Using Temporal Association Rule Mining to Predict Dyadic Rapport in Peer Tutoring (MAM, RL, JC, AO).
- EDM-2017-McBride #simulation #student
- Student Use of Inquiry Simulations in Middle School Science (EM).
- EDM-2017-McBrideVL #simulation #student
- Student Use of Scaffolded Inquiry Simulations in Middle School Science (EM, JMV, MCL).
- EDM-2017-MichalenkoLB #feedback #memory management #network #personalisation
- Personalized Feedback for Open-Response Mathematical Questions using Long Short-Term Memory Networks (JJM, ASL, RGB).
- EDM-2017-MiF #adaptation #recommendation
- Adaptive Sequential Recommendation for Discussion Forums on MOOCs using Context Trees (FM, BF).
- EDM-2017-ParedesHH #behaviour #comprehension #programming #student
- Understanding Student's Reviewing and Reflection Behaviors Using Web-based Programming Grading Assistant (YVMP, PKH, SIHH).
- EDM-2017-PatikornSHBZ #detection #multi
- Using a Single Model Trained across Multiple Experiments to Improve the Detection of Treatment Effects (TP, DS, NTH, JB, JZ).
- EDM-2017-PokrajacSYH #markov #modelling
- Modeling Dormitory Occupancy Using Markov Chains (DDP, KS, DY, TH).
- EDM-2017-RihakP #education #performance #similarity
- Measuring Similarity of Educational Items Using Data on Learners' Performance (JR, RP).
- EDM-2017-ShenC #clustering #student
- Clustering Student Sequential Trajectories Using Dynamic Time Wrapping (SS, MC).
- EDM-2017-ShiPG #analysis #learning #performance
- Using an Additive Factor Model and Performance Factor Analysis to Assess Learning Gains in a Tutoring System to Help Adults with Reading Difficulties (GS, PIPJ, ACG).
- EDM-2017-WanDGP #predict
- Dropout Prediction in MOOCs using Learners' Study Habits Features (HW, JD, XG, DP).
- EDM-2017-WangSLP #learning #programming #student
- Learning to Represent Student Knowledge on Programming Exercises Using Deep Learning (LW, AS, LL, CP).
- EDM-2017-YasudaNKKH #automation #network
- Automatic Scoring Method for Descriptive Test Using Recurrent Neural Network (KY, IN, HK, HK, MH).
- ICPC-2017-AlexandruPG #behaviour #parsing
- Replicating parser behavior using neural machine translation (CVA, SP, HCG), pp. 316–319.
- ICPC-2017-HatanoM #compilation #industrial
- Removing code clones from industrial systems using compiler directives (TH, AM), pp. 336–345.
- ICSME-2017-ChaparroFM #behaviour #debugging #locality #query
- Using Observed Behavior to Reformulate Queries during Text Retrieval-based Bug Localization (OC, JMF, AM), pp. 376–387.
- ICSME-2017-DeshmukhMPSD #debugging #learning #retrieval #towards
- Towards Accurate Duplicate Bug Retrieval Using Deep Learning Techniques (JD, KMA, SP, SS, ND), pp. 115–124.
- ICSME-2017-Gupta #maintenance #mining #predict #process
- Improving Software Maintenance Using Process Mining and Predictive Analytics (MG0), pp. 681–686.
- ICSME-2017-HanLXLF #learning #predict
- Learning to Predict Severity of Software Vulnerability Using Only Vulnerability Description (ZH, XL0, ZX, HL, ZF0), pp. 125–136.
- ICSME-2017-TerdchanakulHPM #classification #debugging #n-gram
- Bug or Not? Bug Report Classification Using N-Gram IDF (PT, HH, PP, KM), pp. 534–538.
- MSR-2017-CartaxoPRKSSS
- Using Q&A websites as a method for assessing systematic reviews (BC, GP0, DMR, FK, RESS, FQBdS, SS), pp. 238–242.
- MSR-2017-NiL #classification #effectiveness #predict
- Cost-effective build outcome prediction using cascaded classifiers (AN, ML0), pp. 455–458.
- MSR-2017-RahmanRK #code review #developer #experience #overview #predict
- Predicting usefulness of code review comments using textual features and developer experience (MMR0, CKR, RGK), pp. 215–226.
- MSR-2017-RajbahadurWKH #classification #fault #modelling
- The impact of using regression models to build defect classifiers (GKR, SW0, YK, AEH), pp. 135–145.
- SANER-2017-DurieuxCSM #exception #generative #metaprogramming #null #pointer
- Dynamic patch generation for null pointer exceptions using metaprogramming (TD, BC, LS, MM), pp. 349–358.
- SANER-2017-LaverdiereM #modelling #security
- Computing counter-examples for privilege protection losses using security models (MAL, EM), pp. 240–249.
- SANER-2017-LiuLNB #fault #locality #modelling #predict #search-based #testing
- Improving fault localization for Simulink models using search-based testing and prediction models (BL, L, SN, LCB), pp. 359–370.
- SANER-2017-TangL #approach #mining #named #novel #probability
- StiCProb: A novel feature mining approach using conditional probability (YT, HL), pp. 45–55.
- SCAM-2017-0008SMOBL #analysis #consistency #identifier
- Investigating the Use of Code Analysis and NLP to Promote a Consistent Usage of Identifiers (BL0, SS, AM, RO, GB, ML), pp. 81–90.
- IFM-2017-AronisFS #model checking #testing #verification
- Testing and Verifying Chain Repair Methods for Corfu Using Stateless Model Checking (SA, SLF, KS), pp. 227–242.
- IFM-2017-FerreiraJMB #authentication #case study #coq #linux #quality
- Certified Password Quality - A Case Study Using Coq and Linux Pluggable Authentication Modules (JFF, SAJ, AM, PJB), pp. 407–421.
- IFM-2017-KovalovLGL #network #smt
- Task-Node Mapping in an Arbitrary Computer Network Using SMT Solver (AK, EL, AG, DL), pp. 177–191.
- SEFM-2017-TomascoN0TP #abstraction #design #memory management #modelling
- Using Shared Memory Abstractions to Design Eager Sequentializations for Weak Memory Models (ET, TLN, BF0, SLT, GP), pp. 185–202.
Haskell-2017-WiegleyD #coq #haskell #performance- Using Coq to write fast and correct Haskell (JW, BD), pp. 52–62.
- ICFP-2017-AuerbachHMSS #case study #compilation #coq #experience #prototype #query
- Prototyping a query compiler using Coq (experience report) (JSA, MH, LM, AS, JS), p. 15.
- AIIDE-2017-BunianCCE #behaviour #difference #game studies #modelling
- Modeling Individual Differences in Game Behavior Using HMM (SB, AC, RCC, MSEN), pp. 158–164.
- AIIDE-2017-FarrellW #interactive
- Influencing User Choices in Interactive Narratives Using Indexter's Pairwise Event Salience Hypothesis (RF, SGW), pp. 37–42.
- AIIDE-2017-FarrellW17a #semantics
- Causal Link Semantics for Narrative Planning Using Numeric Fluents (RF, SGW), pp. 193–199.
- AIIDE-2017-ViljanenAHP
- A/B-Test of Retention and Monetization Using the Cox Model (MV, AA, JH, TP), pp. 248–254.
- CHI-PLAY-2017-BoweyM #game studies #prototype
- Those are not the Stories you are Looking For: Using Text Prototypes to Evaluate Game Narratives Early (JTB, RLM), pp. 265–276.
- CHI-PLAY-2017-Peddycord-LiuCK #game studies #question #student #what
- Using Serious Game Analytics to Inform Digital Curricular Sequencing: What Math Objective Should Students Play Next? (ZPL, CC, SK, TB, CFL, TR), pp. 195–204.
- CIG-2017-ApeldoornV #game studies #knowledge base
- Measuring strategic depth in games using hierarchical knowledge bases (DA, VV), pp. 9–16.
- CIG-2017-BaldwinDFH #design pattern #game studies #generative
- Mixed-initiative procedural generation of dungeons using game design patterns (AB0, SD, JMF, JH), pp. 25–32.
- CIG-2017-BrownA #game studies #multi
- Using multiple worlds for multiple agent roles in games (JAB, DA), pp. 37–44.
- CIG-2017-BurnsT #detection #game studies
- Detecting flow in games using facial expressions (AB, JRT), pp. 45–52.
- CIG-2017-JiangHT #generative
- Procedural generation of angry birds fun levels using pattern-struct and preset-model (YJ0, TH, RT), pp. 154–161.
- CIG-2017-JustesenR #learning
- Learning macromanagement in starcraft from replays using deep learning (NJ, SR), pp. 162–169.
- CIG-2017-MinK #game studies #learning #visual notation
- Learning to play visual doom using model-free episodic control (BJM, KJK), pp. 223–225.
- CIG-2017-OonishiI #game studies #learning
- Improving generalization ability in a puzzle game using reinforcement learning (HO, HI), pp. 232–239.
- CIG-2017-PhucNK #behaviour #learning #statistics
- Learning human-like behaviors using neuroevolution with statistical penalties (LHP, KN, KI), pp. 207–214.
- CIG-2017-SilvaVT #game studies #monte carlo
- Using Monte Carlo tree search and google maps to improve game balancing in location-based games (LFMS, WV, FT), pp. 215–222.
- CIG-2017-SnodgrassO #generative #multi
- Procedural level generation using multi-layer level representations with MdMCs (SS, SO), pp. 280–287.
- FDG-2017-Abuzuraiq #clustering #constraints #generative #graph #morphism #on the
- On using graph partitioning with isomorphism constraint in procedural content generation (AMA), p. 10.
- FDG-2017-AllartLPGN #analysis #game studies #motivation #video
- Difficulty influence on motivation over time in video games using survival analysis (TA, GL, MP, AG, SN), p. 6.
- FDG-2017-CampbellV
- Exploration in NetHack using occupancy maps (JC, CV), p. 4.
- FDG-2017-CleghernLOR #modelling #predict
- Predicting future states in DotA 2 using value-split models of time series attribute data (ZC, SL, OYÖ, DLR), p. 10.
- FDG-2017-Mawhorter #case study #generative #performance #product line #representation
- Efficiency, realism, and representation in generated content: a case study using family tree generation (PAM), p. 4.
- FDG-2017-MelcerI17a #challenge #collaboration #education #game studies #programming
- Embodiment, collaboration, and challenge in educational programming games: exploring use of tangibles and mouse (EFM, KI), p. 6.
- FDG-2017-MurrayMW #graph #interactive
- Proposal for analyzing player emotions in an interactive narrative using story intention graphs (JTM, MM, NWF), p. 4.
- FDG-2017-SeguraIBW #design
- Design, appropriation, and use of technology in larps (EMS, KI, JB, AW), p. 4.
- VS-Games-2017-FerkovaZUM #database #image #re-engineering
- Single image reconstruction of human faces using database of depth images (ZF, MZ, PU, PM), pp. 109–116.
- VS-Games-2017-KontadakisCPM #3d #low cost
- Gamified 3D orthopaedic rehabilitation using low cost and portable inertial sensors (GK, DC, DP, KM), pp. 165–168.
- CIKM-2017-BouadjenekVZ #biology #learning #sequence
- Learning Biological Sequence Types Using the Literature (MRB, KV, JZ), pp. 1991–1994.
- CIKM-2017-BrayteeLCK #correlation #feature model #multi
- Multi-Label Feature Selection using Correlation Information (AB, WL0, DRC, PJK), pp. 1649–1656.
- CIKM-2017-ChavaryEL #mining #network
- Summarizing Significant Changes in Network Traffic Using Contrast Pattern Mining (EAC, SME, CL), pp. 2015–2018.
- CIKM-2017-DasMBS #word
- Estimating Event Focus Time Using Neural Word Embeddings (SD, AM, KB, VS), pp. 2039–2042.
- CIKM-2017-DhakadDBDKM #named #process
- SOPER: Discovering the Influence of Fashion and the Many Faces of User from Session Logs using Stick Breaking Process (LD, MKD, CB, SD, MK, VM), pp. 1609–1618.
- CIKM-2017-DingLHM #fault tolerance #performance #recommendation
- Efficient Fault-Tolerant Group Recommendation Using alpha-beta-core (DD, HL, ZH0, NM), pp. 2047–2050.
- CIKM-2017-GarciaM #energy #network
- Inferring Appliance Energy Usage from Smart Meters using Fully Convolutional Encoder Decoder Networks (FCCG, EQBM), pp. 2075–2078.
- CIKM-2017-GaurBB #graph #query
- Tracking the Impact of Fact Deletions on Knowledge Graph Queries using Provenance Polynomials (GG, SJB, AB0), pp. 2079–2082.
- CIKM-2017-GuptaLHA #induction #sequence #taxonomy
- Taxonomy Induction Using Hypernym Subsequences (AG, RL, HH, KA), pp. 1329–1338.
- CIKM-2017-HalderKS #concurrent #health #recommendation #thread #topic
- Health Forum Thread Recommendation Using an Interest Aware Topic Model (KH, MYK, KS), pp. 1589–1598.
- CIKM-2017-KhandpurJJ0LR #crowdsourcing #detection #social #social media
- Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media (RPK, TJ, STKJ, GW0, CTL, NR), pp. 1049–1057.
- CIKM-2017-KhoaAW #analysis #framework #incremental #maintenance
- Smart Infrastructure Maintenance Using Incremental Tensor Analysis: Extended Abstract (NLDK, AA, YW), pp. 959–967.
- CIKM-2017-KimJY #multi #online
- Construction of a National Scale ENF Map using Online Multimedia Data (HK, YBJ, JWY), pp. 19–28.
- CIKM-2017-KwonKS #recognition #robust
- A Robust Named-Entity Recognition System Using Syllable Bigram Embedding with Eojeol Prefix Information (SK, YK, JS), pp. 2139–2142.
- CIKM-2017-MehrotraY #learning #query
- Task Embeddings: Learning Query Embeddings using Task Context (RM, EY), pp. 2199–2202.
- CIKM-2017-Ni0ZYM #fine-grained #learning #metric #similarity
- Fine-grained Patient Similarity Measuring using Deep Metric Learning (JN, JL0, CZ, DY, ZM), pp. 1189–1198.
- CIKM-2017-ParmarBBK #online #process
- Forecasting Ad-Impressions on Online Retail Websites using Non-homogeneous Hawkes Processes (KP, SB, SB, SK), pp. 1089–1098.
- CIKM-2017-ProskurniaM0AC #detection #documentation #performance #topic
- Efficient Document Filtering Using Vector Space Topic Expansion and Pattern-Mining: The Case of Event Detection in Microposts (JP, RM, CC0, KA, PCM), pp. 457–466.
- CIKM-2017-TengLW #detection #learning #multi #network
- Anomaly Detection in Dynamic Networks using Multi-view Time-Series Hypersphere Learning (XT, YRL, XW), pp. 827–836.
- CIKM-2017-VellosoD #approach #web
- Extracting Records from the Web Using a Signal Processing Approach (RPV, CFD), pp. 197–206.
- CIKM-2017-WangCL #graph #twitter
- Using Knowledge Graphs to Explain Entity Co-occurrence in Twitter (YW, MJC, YFL), pp. 2351–2354.
- CIKM-2017-YeHHCLQS #classification
- Nationality Classification Using Name Embeddings (JY, SH, YH, BC, ML, HQ, SS), pp. 1897–1906.
- CIKM-2017-ZhangH #ambiguity #graph #network
- Name Disambiguation in Anonymized Graphs using Network Embedding (BZ, MAH), pp. 1239–1248.
- CIKM-2017-ZhangJT #retrieval
- Temporal Analog Retrieval using Transformation over Dual Hierarchical Structures (YZ, AJ, KT), pp. 717–726.
- CIKM-2017-ZhiSLZ0 #database #named #realtime #verification #web
- ClaimVerif: A Real-time Claim Verification System Using the Web and Fact Databases (SZ, YS, JL, CZ0, JH0), pp. 2555–2558.
- ECIR-2017-AletrasM #image #network #topic
- Labeling Topics with Images Using a Neural Network (NA, AM), pp. 500–505.
- ECIR-2017-ArguelloA0 #performance #predict #query
- Using Query Performance Predictors to Reduce Spoken Queries (JA, SA, FD0), pp. 27–39.
- ECIR-2017-AyadiKHDJ #image #learning
- Learning to Re-rank Medical Images Using a Bayesian Network-Based Thesaurus (HA, MTK, JXH, MD, MBJ), pp. 160–172.
- ECIR-2017-BaruaP #classification #query
- Named Entity Classification Using Search Engine's Query Suggestions (JB, DP), pp. 612–618.
- ECIR-2017-J0V #twitter
- Improving Tweet Representations Using Temporal and User Context (GJ, MG0, VV), pp. 575–581.
- ECIR-2017-McDonaldMO #classification #semantics #word
- Enhancing Sensitivity Classification with Semantic Features Using Word Embeddings (GM, CM, IO), pp. 450–463.
- ECIR-2017-ParamitaCG #similarity #wiki
- Using Section Headings to Compute Cross-Lingual Similarity of Wikipedia Articles (MLP, PDC, RJG), pp. 633–639.
- ICML-2017-BernsteinMSSHM #learning #modelling #visual notation
- Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models (GB, RM, TS, DS, MH, GM), pp. 478–487.
- ICML-2017-BoraJPD #generative #modelling
- Compressed Sensing using Generative Models (AB, AJ, EP, AGD), pp. 537–546.
- ICML-2017-ChenKB #equation #identification #linear #modelling #testing
- Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables (BC, DK, EB), pp. 757–766.
- ICML-2017-ChouMS #learning #policy #probability
- Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution (PWC, DM, SAS), pp. 834–843.
- ICML-2017-EcksteinGK #generative
- Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement (JE, NG, AK), pp. 1059–1067.
- ICML-2017-JaderbergCOVGSK #interface
- Decoupled Neural Interfaces using Synthetic Gradients (MJ, WMC, SO, OV, AG, DS, KK), pp. 1627–1635.
- ICML-2017-Kallus #clustering #personalisation #recursion
- Recursive Partitioning for Personalization using Observational Data (NK), pp. 1789–1798.
- ICML-2017-MhammediHRB #network #orthogonal #performance
- Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections (ZM, ADH, AR, JB0), pp. 2401–2409.
- ICML-2017-MollaysaSK #modelling
- Regularising Non-linear Models Using Feature Side-information (AM, PS, AK), pp. 2508–2517.
- ICML-2017-NguyenLST #machine learning #named #novel #probability #problem #recursion
- SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient (LMN, JL, KS, MT), pp. 2613–2621.
- ICML-2017-SchlegelPCW #adaptation #kernel #online
- Adapting Kernel Representations Online Using Submodular Maximization (MS, YP, JC, MW), pp. 3037–3046.
- ICML-2017-Villacampa-Calvo #classification #multi #process #scalability
- Scalable Multi-Class Gaussian Process Classification using Expectation Propagation (CVC, DHL), pp. 3550–3559.
- ICML-2017-YangHSB #modelling
- Improved Variational Autoencoders for Text Modeling using Dilated Convolutions (ZY, ZH, RS, TBK), pp. 3881–3890.
- KDD-2017-AgarwalBSJ #effectiveness #evaluation #feedback #multi
- Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers (AA, SB0, TS, TJ), pp. 687–696.
- KDD-2017-AlbertKG #identification #network #scalability
- Using Convolutional Networks and Satellite Imagery to Identify Patterns in Urban Environments at a Large Scale (AA, JK, MCG), pp. 1357–1366.
- KDD-2017-ChamberlainCLPD #predict
- Customer Lifetime Value Prediction Using Embeddings (BPC, ÂC, CHBL, RP, MPD), pp. 1753–1762.
- KDD-2017-EmraniMX #learning #multi
- Prognosis and Diagnosis of Parkinson's Disease Using Multi-Task Learning (SE, AM, WX), pp. 1457–1466.
- KDD-2017-FoxAJPW
- Contextual Motifs: Increasing the Utility of Motifs using Contextual Data (IF, LA, MJ, RPB, JW), pp. 155–164.
- KDD-2017-LiHG #concept #enterprise #spreadsheet
- Discovering Enterprise Concepts Using Spreadsheet Tables (KL, YH, KG), pp. 1873–1882.
- KDD-2017-MaurusP #detection
- Let's See Your Digits: Anomalous-State Detection using Benford's Law (SM, CP), pp. 977–986.
- KDD-2017-MottiniA #network #pointer #predict
- Deep Choice Model Using Pointer Networks for Airline Itinerary Prediction (AM, RAA), pp. 1575–1583.
- KDD-2017-WoodsAMM #feedback #modelling #predict
- Formative Essay Feedback Using Predictive Scoring Models (BW, DA, SM, EM), pp. 2071–2080.
- ICMT-2017-BurguenoHVG #modelling #testing
- Testing Transformation Models Using Classifying Terms (LB, FH, AV, MG), pp. 69–85.
- ICMT-2017-GerkingSB #imperative
- Reducing the Verbosity of Imperative Model Refinements by Using General-Purpose Language Facilities (CG, DS, IB), pp. 19–34.
- OOPSLA-2017-MazinanianKTD #comprehension #java
- Understanding the use of lambda expressions in Java (DM, AK, NT, DD), p. 31.
- OOPSLA-2017-WangDS #automaton #finite #synthesis
- Synthesis of data completion scripts using finite tree automata (XW0, ID, RS), p. 26.
- AdaEurope-2017-JeongYB #transaction
- Lock Elision for Protected Objects Using Intel Transactional Synchronization Extensions (SJ, SY, BB), pp. 121–136.
- PADL-2017-MantadelisR #logic #probability
- Using Iterative Deepening for Probabilistic Logic Inference (TM, RR0), pp. 198–213.
PEPM-2017-HengleinR #dynamic analysis #parsing expression grammar- PEG parsing in less space using progressive tabling and dynamic analysis (FH, UTR), pp. 35–46.
- PEPM-2017-WolffH #typescript
- Refining types using type guards in TypeScript (IGdW, JH), pp. 111–122.
- PLDI-2017-HuD #automation #transducer
- Automatic program inversion using symbolic transducers (QH, LD), pp. 376–389.
- PLDI-2017-PetrashkoLO #compilation #composition #named #performance #program transformation
- Miniphases: compilation using modular and efficient tree transformations (DP, OL, MO), pp. 201–216.
- POPL-2017-SrikanthSH #complexity #theorem #verification
- Complexity verification using guided theorem enumeration (AS, BS, WRH), pp. 639–652.
QAPL-2017-LidmanS #fuzzy #logic #program analysis- Bridging Static and Dynamic Program Analysis using Fuzzy Logic (JL, JS), pp. 111–126.
- SAS-2017-OuadjaoutM #communication #markov #protocol #static analysis
- Quantitative Static Analysis of Communication Protocols Using Abstract Markov Chains (AO, AM), pp. 277–298.
- ASE-2017-Abdelrasoul #order #random #scheduling
- Promoting secondary orders of event pairs in randomized scheduling using a randomized stride (MA), pp. 741–752.
- ASE-2017-JiangAM #automation #commit #generative
- Automatically generating commit messages from diffs using neural machine translation (SJ, AA, CM), pp. 135–146.
- ASE-2017-KrugerNRAMBGGWD #developer #encryption #named
- CogniCrypt: supporting developers in using cryptography (SK, SN, MR, KA0, MM, EB, FG, FG0, CW, DD, RK), pp. 931–936.
- ASE-2017-LinZZX #concept #retrieval #source code
- Improving software text retrieval using conceptual knowledge in source code (ZL, YZ, JZ, BX), pp. 123–134.
- ASE-2017-NguyenDV #invariant #named
- SymInfer: inferring program invariants using symbolic states (TN, MBD, WV), pp. 804–814.
- ASE-2017-RahmanR #concept #documentation #query
- Improved query reformulation for concept location using CodeRank and document structures (MMR, CKR), pp. 428–439.
- ASE-2017-Sultana #metric #predict #towards
- Towards a software vulnerability prediction model using traceable code patterns and software metrics (KZS), pp. 1022–1025.
- ASE-2017-SunCWB
- Improving missing issue-commit link recovery using positive and unlabeled data (YS, CC, QW0, BWB), pp. 147–152.
- ESEC-FSE-2017-Abdalkareem #developer #perspective
- Reasons and drawbacks of using trivial npm packages: the developers' perspective (RA), pp. 1062–1064.
- ESEC-FSE-2017-LabuschagneIH #case study #cost analysis #integration #java #testing
- Measuring the cost of regression testing in practice: a study of Java projects using continuous integration (AL, LI, RH), pp. 821–830.
- ESEC-FSE-2017-MaggioPFH #automation #multi
- Automated control of multiple software goals using multiple actuators (MM, AVP, AF, HH), pp. 373–384.
- ESEC-FSE-2017-NairMSA
- Using bad learners to find good configurations (VN, TM, NS, SA), pp. 257–267.
- ESEC-FSE-2017-Oliveira #architecture #co-evolution #dependence #fine-grained #named #refactoring
- DRACO: discovering refactorings that improve architecture using fine-grained co-change dependencies (MCdO0), pp. 1018–1021.
- ESEC-FSE-2017-Schramm #automation #heuristic #performance #program repair
- Improving performance of automatic program repair using learned heuristics (LS), pp. 1071–1073.
- ESEC-FSE-2017-Wang #adaptation #nondeterminism #re-engineering #search-based #self
- Using search-based software engineering to handle the changes with uncertainties for self-adaptive systems (LW), pp. 1014–1017.
- ESEC-FSE-2017-YiAKTR #automation #program repair #programming
- A feasibility study of using automated program repair for introductory programming assignments (JY, UZA, AK, SHT, AR), pp. 740–751.
- ICSE-2017-0004CC #learning #semantics #traceability
- Semantically enhanced software traceability using deep learning techniques (JG0, JC, JCH), pp. 3–14.
- GPCE-2017-GrebeYG #compilation #domain-specific language #haskell
- Rewriting a shallow DSL using a GHC compiler extension (MG, DY, AG), pp. 246–258.
- SLE-2017-BrambillaCIM #crowdsourcing #domain-specific language
- Better call the crowd: using crowdsourcing to shape the notation of domain-specific languages (MB, JC, JLCI, AM), pp. 129–138.
- ASPLOS-2017-GeCJ #control flow #named
- GRIFFIN: Guarding Control Flows Using Intel Processor Trace (XG, WC, TJ), pp. 585–598.
- ASPLOS-2017-RenLDQWLQY #named #network #probability
- SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing (AR, ZL0, CD, QQ, YW, JL0, XQ, BY0), pp. 405–418.
- CASE-2017-0013YG #graph #image #optimisation
- Accurate image mosaicing for bridge deck using graph optimization with GPS data (FL0, JY, NG), pp. 1090–1095.
- CASE-2017-CarliD #distributed #grid #monitoring #multi #smarttech
- Using the distributed proximal alternating direction method of multipliers for smart grid monitoring (RC, MD), pp. 418–423.
- CASE-2017-CarliD17a #distributed #energy #programming #scalability
- A decentralized control strategy for energy retrofit planning of large-scale street lighting systems using dynamic programming (RC, MD), pp. 1196–1200.
- CASE-2017-ChenZ #automation #detection #multi
- An automatic seizure detection method using multi-channel EEG signals (SC, XZ0), pp. 94–95.
- CASE-2017-DuHZL #automation #petri net #robust
- Robust control of automated manufacturing systems with complex structures using Petri Nets (ND, HH, YZ0, YL0), pp. 364–369.
- CASE-2017-HuangMY #algorithm #difference #evolution #performance #throughput
- Forecasting of throughput performance using an ARMA model with improved differential evolution algorithm (JTH, YM, YY), pp. 376–381.
- CASE-2017-InuiKU #gpu #parallel #performance
- Fast extraction of cutter engagement features by using the parallel processing function of a GPU (MI, MK, NU), pp. 668–673.
- CASE-2017-KeL #mobile #predict #robust #visual notation
- Visual servoing of constrained differential-drive mobile robots using robust tube-based predictive control (FK, ZL0), pp. 1073–1078.
- CASE-2017-KongN #approach #fault #predict
- A practical yield prediction approach using inline defect metrology data for system-on-chip integrated circuits (YK, DN), pp. 744–749.
- CASE-2017-LeeJFBGBL #analysis #modelling #process #simulation
- Modeling and analysis of postoperative intervention process for total joint replacement patients using simulations (HKL, RJ, YF, PAB, JG, CB, JL), pp. 568–573.
- CASE-2017-LiangMLLG #automation #industrial #learning
- Using dVRK teleoperation to facilitate deep learning of automation tasks for an industrial robot (JL, JM, ML, PL, KG), pp. 1–8.
- CASE-2017-LiLHTCLW #analysis
- The mechanism analysis of bipolar vessel sealing in vitro using EDM model (LL, LL, ZH, MT, RC, HL, JW), pp. 813–818.
- CASE-2017-OhKKSC
- Calibration of 6 axis force/torque sensor by using deep-learning method (HSO, GK, UK, JKS, HRC), pp. 1316–1317.
- CASE-2017-QinLG #data analysis #energy #internet
- Data analytics for energy consumption of digital manufacturing systems using Internet of Things method (JQ, YL, RIG), pp. 482–487.
- CASE-2017-SugimotoMMM #3d #modelling
- A 3D block printer using toy bricks for various models (CS, YM, TM, SM), pp. 958–963.
- CASE-2017-SunLYLL #simulation #smarttech
- Muscle control of fore-aft and vertical body center of mass accelerations of human slip recovery gait: A simulation study using wearable sensor shoes (WS, GL, JY, QL, TL0), pp. 1408–1413.
- CASE-2017-SunLZJ #framework #functional #learning
- Exploring functional variant using a deep learning framework (TS, ZL, XMZ, RJ), pp. 98–99.
- CASE-2017-ToneS
- A ferrofluid-based robotic sheet for liquid manipulation by using vibration control (TT, KS), pp. 776–781.
- CASE-2017-WangOLC #big data #problem #self
- Capacitated competitive facility location problem of self-collection lockers by using public big data (YW0, TO, LHL, EPC), p. 1344.
- CASE-2017-WangW #approach #constraints #higher-order #programming
- Resolve reactive robot control with perturbed constraints using a second order cone programming approach (YW, LW), pp. 124–129.
- CASE-2017-WangZLHSMGY #online
- Smart control of indoor thermal environment based on online learned thermal comfort model using infrared thermal imaging (FW, BZ, RL, DH, ZS, SM, ZG, WY), pp. 924–925.
- CASE-2017-Xiao #constraints
- Selecting the best system using transient means with sequential sampling constraints (HX), p. 1052.
- CASE-2017-ZhangJ17a #estimation
- An occupancy distribution estimation method using the surveillance cameras in buildings (CZ, QSJ), pp. 894–899.
- CC-2017-ShirakoHS #gpu #parallel
- Optimized two-level parallelization for GPU accelerators using the polyhedral model (JS, AH, VS), pp. 22–33.
- CGO-2017-SenguptaCBK #bound #hardware #memory management #named #transaction
- Legato: end-to-end bounded region serializability using commodity hardware transactional memory (AS, MC, MDB, MK0), pp. 1–13.
- ESOP-2017-0001P #source code #syntax
- Programs Using Syntax with First-Class Binders (FF0, BP), pp. 504–529.
- ESOP-2017-KhyzhaDGP #partial order #proving
- Proving Linearizability Using Partial Orders (AK, MD, AG, MJP), pp. 639–667.
- ESOP-2017-KopS #complexity #higher-order #nondeterminism #power of #programming
- The Power of Non-determinism in Higher-Order Implicit Complexity - Characterising Complexity Classes Using Non-deterministic Cons-Free Programming (CK, JGS), pp. 668–695.
- FASE-2017-LeblebiciAS #consistency #graph grammar #linear #optimisation
- Inter-model Consistency Checking Using Triple Graph Grammars and Linear Optimization Techniques (EL, AA, AS), pp. 191–207.
- CAV-2017-Vafeiadis #consistency #logic #memory management #verification
- Program Verification Under Weak Memory Consistency Using Separation Logic (VV), pp. 30–46.
- CAV-2017-BouajjaniEEM #proving #simulation
- Proving Linearizability Using Forward Simulations (AB, ME, CE, SOM), pp. 542–563.
- CAV-2017-ReynoldsWBBLT #scalability #string
- Scaling Up DPLL(T) String Solvers Using Context-Dependent Simplification (AR, MW, CWB, DB, TL, CT), pp. 453–474.
- ICST-2017-ChanWSPS #analysis #concurrent #fault #invariant #multi #named #source code #thread
- IPA: Error Propagation Analysis of Multi-Threaded Programs Using Likely Invariants (AC, SW0, HS, KP, NS), pp. 184–195.
- ICST-2017-ConverseOK #execution #generative #semantics #symbolic computation #testing
- Non-Semantics-Preserving Transformations for Higher-Coverage Test Generation Using Symbolic Execution (HC, OO, SK), pp. 241–252.
- ICST-2017-DarkeCCV #abstraction #bound #model checking #performance #proving #safety
- Efficient Safety Proofs for Industry-Scale Code Using Abstractions and Bounded Model Checking (PD, BC, AC, RV), pp. 468–475.
- ICST-2017-DiasFFLSSV #concurrent #contract #source code #verification
- Verifying Concurrent Programs Using Contracts (RJD, CF0, JF, JML, AS, DGS, TV), pp. 196–206.
- ICST-2017-LinWC #semantics #similarity #testing #web
- Using Semantic Similarity in Crawling-Based Web Application Testing (JWL, FW, PC), pp. 138–148.
- ICST-2017-LuckowKP #analysis #complexity
- Symbolic Complexity Analysis Using Context-Preserving Histories (KSL, RK, CSP), pp. 58–68.
- ICST-2017-SunRJB #android #named #runtime #verification #weaving
- ADRENALIN-RV: Android Runtime Verification Using Load-Time Weaving (HS, AR, OJ, WB), pp. 532–539.
- ICST-2017-XuLC #concurrent #data type #debugging #testing
- Using Delta Debugging to Minimize Stress Tests for Concurrent Data Structures (JX, YL, RHC), pp. 35–46.
- ICTSS-2017-HusterSRKR #robust #testing #verification
- Using Robustness Testing to Handle Incomplete Verification Results When Combining Verification and Testing Techniques (SH, JS, JR, TK, WR), pp. 54–70.
- ICTSS-2017-SalvaR #integration #security #testing
- Using Data Integration for Security Testing (SS, LR), pp. 178–194.
- ICTSS-2017-SimosBDGKLW #combinator #execution #framework #testing
- Testing TLS Using Combinatorial Methods and Execution Framework (DES, JB, FD, BG, KK, YL, FW), pp. 162–177.
- VMCAI-2017-BotbolCG #communication #process #static analysis #transducer
- Static Analysis of Communicating Processes Using Symbolic Transducers (VB, EC, TLG), pp. 73–90.
- VMCAI-2017-FerraraT0K #abstract interpretation #fault
- Using Abstract Interpretation to Correct Synchronization Faults (PF, OT, PL0, EK), pp. 187–208.
- VMCAI-2017-GuW #analysis #float #source code
- Stabilizing Floating-Point Programs Using Provenance Analysis (YG, TW), pp. 228–245.
- VMCAI-2017-MonatM #abstract interpretation #abstraction #concurrent #precise #relational #source code #thread
- Precise Thread-Modular Abstract Interpretation of Concurrent Programs Using Relational Interference Abstractions (RM, AM), pp. 386–404.
- VMCAI-2017-OzeriPRS #abstract interpretation
- Conjunctive Abstract Interpretation Using Paramodulation (OO, OP, NR, MS), pp. 442–461.
CBSE-2016-CrnkovicMMS #architecture #component #cyber-physical #on the- On the Use of Component-Based Principles and Practices for Architecting Cyber-Physical Systems (IC, IM, HM, MS), pp. 23–32.
- CBSE-2016-StevaneticZ #architecture #component #experience #metric #modelling
- Exploring the Understandability of Components in Architectural Component Models Using Component Level Metrics and Participants' Experience (SS, UZ), pp. 1–6.
- ECSA-2016-ErsoyKAS #architecture #clustering #re-engineering
- Using Hypergraph Clustering for Software Architecture Reconstruction of Data-Tier Software (EE, KK, MA, HS), pp. 326–333.
QoSA-2016-LehrigB #as a service #case study #modelling #performance- Using Performance Models for Planning the Redeployment to Infrastructure-as-a-Service Environments: A Case Study (SL, SB0), pp. 11–20.
WICSA-2016-KazmanCHH #architecture #design #summary #tutorial- Tutorial Summary for Designing Software Architectures Using ADD 3.0 (RK, HC, SH, OH), p. 253.
- WICSA-2016-SobernigZ #architecture #design
- Distilling Architectural Design Decisions and Their Relationships Using Frequent Item-Sets (SS, UZ), pp. 61–70.
- JCDL-2016-BornandBS #classification
- Routing Memento Requests Using Binary Classifiers (NJB, LB, HVdS), pp. 63–72.
- JCDL-2016-Frick #framework #library #platform #research
- The State of Practice and Use of Digital Collections: The Digital Public Library of America as a platform for research (RF), p. 3.
- JCDL-2016-JettNCPD #comparative #library #metadata #ontology #overview
- Enhancing Scholarly Use of Digital Libraries: A Comparative Survey and Review of Bibliographic Metadata Ontologies (JJ, TNF, TWC, KRP, JSD), pp. 35–44.
- CSEET-2016-FreitasSM #learning #student
- Using an Active Learning Environment to Increase Students' Engagement (SAAdF, WCMPS, GM), pp. 232–236.
- CSEET-2016-GeorgasPM #architecture #learning #runtime #visualisation
- Supporting Software Architecture Learning Using Runtime Visualization (JCG, JDP, MJM), pp. 101–110.
- CSEET-2016-LiebelHS #education #industrial #modelling #tool support
- Impact of the Use of Industrial Modelling Tools on Modelling Education (GL, RH, JPS), pp. 18–27.
- CSEET-2016-SrinivasanLY #comprehension #diagrams #object-oriented #programming #sequence chart
- Enhancing Object-Oriented Programming Comprehension Using Optimized Sequence Diagram (MS, YL, JY), pp. 81–85.
- EDM-2016-ChenDP #diagrams #problem
- Examining the necessity of problem diagrams using MOOC AB experiments (ZC, ND, DEP), pp. 579–580.
- EDM-2016-FouhFHKS #data analysis #data type #topic
- Investigating Difficult Topics in a Data Structures Course Using Item Response Theory and Logged Data Analysis (EF, MFF, SH, KHK, CAS), pp. 370–375.
- EDM-2016-Kyrilov #automation #feedback #programming #reasoning
- Using Case-Based Reasoning to Automatically Generate High-Quality Feedback for Programming Exercises (AK), pp. 669–671.
- EDM-2016-LiuDS #data type #data-driven #multi #towards
- Beyond Log Files: Using Multi-Modal Data Streams Towards Data-Driven KC Model Improvement (RL0, JLD, JCS), pp. 436–441.
- EDM-2016-Mojarad #performance #student
- Studying Assignment Size and Student Performance Using Propensity Score Matching (SM), pp. 701–702.
- EDM-2016-NgHLK #learning #modelling #sequence
- Modelling the way: Using action sequence archetypes to differentiate learning pathways from learning outcomes (KHRN, KH, KL, AWHK), pp. 167–174.
- EDM-2016-NogaitoYK #automation #case study #similarity #testing
- Study on Automatic Scoring of Descriptive Type Tests using Text Similarity Calculations (IN, KY, HK), pp. 616–617.
- EDM-2016-Penteado #assessment #data mining #estimation #mining #scalability #semantics
- Estimation of prerequisite skills model from large scale assessment data using semantic data mining (BEP), pp. 675–677.
- EDM-2016-RaffertyJG #feedback #personalisation
- Using Inverse Planning for Personalized Feedback (ANR, RJ, TLG), pp. 472–477.
- EDM-2016-RenRJ #modelling #multi #performance #predict
- Predicting Performance on MOOC Assessments using Multi-Regression Models (ZR, HR, AJ), pp. 484–489.
- EDM-2016-Yee-KingGd #collaboration #learning #metric #online #predict #social #student
- Predicting student grades from online, collaborative social learning metrics using K-NN (MYK, AGR, Md), pp. 654–655.
- EDM-2016-ZhengKTG #clustering #concept #physics
- Soft Clustering of Physics Misconceptions Using a Mixed Membership Model (GZ, SK, YT, AG), pp. 658–659.
- ICPC-2016-MetcalfFYF #interactive #parametricity #static analysis
- Extracting configuration parameter interactions using static analysis (CAM, FF, TY, JF), pp. 1–4.
- ICSME-2016-AndersonDS #testing
- Customized Regression Testing Using Telemetry Usage Patterns (JA, HD, SS), pp. 572–581.
- ICSME-2016-GopinathWHK #fault #machine learning
- Repairing Intricate Faults in Code Using Machine Learning and Path Exploration (DG, KW, JH, SK), pp. 453–457.
- ICSME-2016-KargenS #towards
- Towards Accurate Binary Correspondence Using Runtime-Observed Values (UK, NS), pp. 438–442.
- ICSME-2016-KhourySH #comprehension #principle
- Key Elements Extraction and Traces Comprehension Using Gestalt Theory and the Helmholtz Principle (RK, LS, AHL), pp. 478–482.
- ICSME-2016-LevinY #developer #maintenance #predict #process #semantics
- Using Temporal and Semantic Developer-Level Information to Predict Maintenance Activity Profiles (SL, AY), pp. 463–467.
- ICSME-2016-NguyenNN #fine-grained #source code #topic
- Using Topic Model to Suggest Fine-Grained Source Code Changes (HAN, ATN0, TNN), pp. 200–210.
- ICSME-2016-PalombaZFLO #debugging #performance #predict #smell
- Smells Like Teen Spirit: Improving Bug Prediction Performance Using the Intensity of Code Smells (FP, MZ, FAF, ADL, RO), pp. 244–255.
- ICSME-2016-XiaBLL #automation #case study #debugging #fault #harmful #locality #scalability #user study
- “Automated Debugging Considered Harmful” Considered Harmful: A User Study Revisiting the Usefulness of Spectra-Based Fault Localization Techniques with Professionals Using Real Bugs from Large Systems (XX0, LB, DL0, SL), pp. 267–278.
- MSR-2016-DamevskiCSP #developer #interactive #markov
- Interactive exploration of developer interaction traces using a hidden markov model (KD, HC0, DCS, LLP), pp. 126–136.
- MSR-2016-KikasDP #git #predict
- Using dynamic and contextual features to predict issue lifetime in GitHub projects (RK, MD, DP), pp. 291–302.
- MSR-2016-RolfsnesMABB #recommendation
- Improving change recommendation using aggregated association rules (TR, LM, SDA, RB, DWB), pp. 73–84.
- SANER-2016-0029BKT #android #library
- An Investigation into the Use of Common Libraries in Android Apps (LL0, TFB, JK, YLT), pp. 403–414.
- SANER-2016-BorckBSHHJSS #named #source code
- Frankencode: Creating Diverse Programs Using Code Clones (HB, MSB, IJDS, SAH, KH, SJ, AS, MS), pp. 604–608.
- SANER-2016-MazinanianT #css #empirical #preprocessor
- An Empirical Study on the Use of CSS Preprocessors (DM, NT), pp. 168–178.
- SANER-2016-MendesVHS #identification #random
- Identifying Utility Functions Using Random Forests (TM, MTV, ACH, AS), pp. 614–618.
- SANER-2016-NishimuraM #fine-grained
- Supporting Merge Conflict Resolution by Using Fine-Grained Code Change History (YN, KM), pp. 661–664.
- SANER-2016-PanichellaDOPPL #algorithm #search-based
- Parameterizing and Assembling IR-Based Solutions for SE Tasks Using Genetic Algorithms (AP, BD, RO, MDP, DP, ADL), pp. 314–325.
- SANER-2016-RahmanRL #api #automation #crowdsourcing #named #recommendation
- RACK: Automatic API Recommendation Using Crowdsourced Knowledge (MMR0, CKR, DL0), pp. 349–359.
- SANER-2016-ZhengRSLSJBCQB #analysis #hybrid #named
- AutoBench: Finding Workloads That You Need Using Pluggable Hybrid Analyses (YZ, AR, LS, YL0, HS, OJ, LB, LYC, ZQ, WB), pp. 639–643.
- CIAA-2016-StasioMPV #algorithm #game studies
- Solving Parity Games Using an Automata-Based Algorithm (ADS, AM, GP, MYV), pp. 64–76.
- CIAA-2016-WeidemanMBW #ambiguity #automaton #backtracking #behaviour #nondeterminism #regular expression
- Analyzing Matching Time Behavior of Backtracking Regular Expression Matchers by Using Ambiguity of NFA (NW, BvdM, MB, BWW), pp. 322–334.
DLT-2016-Basten #ambiguity #automaton #detection #multi- Context-Free Ambiguity Detection Using Multi-stack Pushdown Automata (HJSB), pp. 1–12.
- FM-2016-CavadaCCRT #design #embedded #energy #modelling
- Model-Based Design of an Energy-System Embedded Controller Using Taste (RC, AC, LC, MR, ST), pp. 741–747.
- FM-2016-StoenescuSPI #analysis #execution #framework #named #symbolic computation
- RIVER: A Binary Analysis Framework Using Symbolic Execution and Reversible x86 Instructions (TS, AS, SP, FI), pp. 779–785.
- FM-2016-VakiliD #finite #logic #similarity
- Finite Model Finding Using the Logic of Equality with Uninterpreted Functions (AV, NAD), pp. 677–693.
- IFM-2016-AntoninoGR #analysis #performance #satisfiability
- Efficient Deadlock-Freedom Checking Using Local Analysis and SAT Solving (PA, TGR, AWR), pp. 345–360.
- IFM-2016-KumarBLDUB #verification
- CloudSDV Enabling Static Driver Verifier Using Microsoft Azure (RK, TB, JL, ND, AU, CB), pp. 523–536.
- IFM-2016-Preoteasa #invariant #logic #pointer #programming #source code #verification
- Verifying Pointer Programs Using Separation Logic and Invariant Based Programming in Isabelle (VP), pp. 457–473.
- IFM-2016-SchutsHV #case study #equivalence #experience #industrial #learning #legacy #refactoring
- Refactoring of Legacy Software Using Model Learning and Equivalence Checking: An Industrial Experience Report (MS, JH, FWV), pp. 311–325.
- SEFM-2016-FeistMP #control flow #execution #symbolic computation
- Guided Dynamic Symbolic Execution Using Subgraph Control-Flow Information (JF, LM, MLP), pp. 76–81.
- SEFM-2016-HusienS #generative #model checking
- Program Generation Using Simulated Annealing and Model Checking (IH, SS), pp. 155–171.
- Haskell-2016-WangNF #algorithm #named #search-based #strict
- Autobahn: using genetic algorithms to infer strictness annotations (YRW, DN, KF), pp. 114–126.
- ICFP-2016-CastroHS #morphism #parallel #pipes and filters #process #reasoning
- Farms, pipes, streams and reforestation: reasoning about structured parallel processes using types and hylomorphisms (DC, KH, SS), pp. 4–17.
- AIIDE-2016-DebkowskiMYYYFK #behaviour #collaboration #game studies #multi #named #online
- Contained: Using Multiplayer Online Games to Quantify Success of Collaborative Group Behavior (DD, AM, NY, LY, YY, SF, MK), pp. 149–154.
- AIIDE-2016-GeibWMKCP #recognition
- Building Helpful Virtual Agents Using Plan Recognition and Planning (CWG, JW, SM, PK, BGWC, RPAP), pp. 162–168.
- AIIDE-2016-GunesSAES #approach #modelling
- A Generic Approach for Player Modeling Using Event-Trait Mapping and Feature Weighting (MAG, GS, UA, OE, SS), pp. 169–175.
- AIIDE-2016-HarrisonR #crowdsourcing #learning
- Learning From Stories: Using Crowdsourced Narratives to Train Virtual Agents (BH, MOR), pp. 183–189.
- AIIDE-2016-SinghDHJPM #network
- Recognizing Actions in Motion Trajectories Using Deep Neural Networks (KYS, NMD, CPH, MJ, KP, BM), pp. 211–217.
- AIIDE-2016-SooLC #monte carlo
- Generate Believable Causal Plots with User Preferences Using Constrained Monte Carlo Tree Search (VWS, CML, THC), pp. 218–224.
- CHI-PLAY-2016-ReinschluesselM #game studies #self
- Using Positive or Negative Reinforcement in Neurofeedback Games for Training Self-Regulation (AVR, RLM), pp. 186–198.
- CHI-PLAY-2016-SavardBW #challenge #collaboration #game studies
- Collaborative Solving in a Human Computing Game Using a Market, Skills and Challenges (OTS, AB, JW), pp. 130–141.
- CHI-PLAY-2016-SharmaTDKJ #artificial reality #game studies
- Evaluating Display Modalities Using a Mixed Reality Game (HNS, ZOT, ID, AK, AJ), pp. 65–77.
- CHI-PLAY-2016-ZayerTF #mobile #named
- PAWdio: Hand Input for Mobile VR using Acoustic Sensing (MAZ, ST, EF), pp. 154–158.
- CIG-2016-Bursztein #learning #statistics
- I am a legend: Hacking hearthstone using statistical learning methods (EB), pp. 1–8.
- CIG-2016-CazenaveLTT #game studies #learning #random
- Learning opening books in partially observable games: Using random seeds in Phantom Go (TC, JL0, FT, OT), pp. 1–7.
- CIG-2016-KiourtK #modelling #social
- Using opponent models to train inexperienced synthetic agents in social environments (CK, DK), pp. 1–4.
- CIG-2016-ParkK #visual notation
- Deep Q-learning using redundant outputs in visual doom (HSP, KJK), pp. 1–2.
- CIG-2016-SephtonCDHS #android #mining #predict
- Using association rule mining to predict opponent deck content in android: Netrunner (NS, PIC, SD, VJH, NHS), pp. 1–8.
- CIG-2016-StanescuBHB #game studies #network #realtime
- Evaluating real-time strategy game states using convolutional neural networks (MS, NAB, AH, MB), pp. 1–7.
- CIG-2016-YooK #algorithm #game studies #video
- Changing video game graphic styles using neural algorithms (BY, KJK), pp. 1–2.
DiGRA-FDG-2016-GoddardM #assembly #design #game studies- Designing Unconventional Use of Conventional Displays in Games: Some Assembly Required (WG, AM).
- DiGRA-FDG-2016-LimLH #approach #bottom-up #category theory #clustering #image #social
- Discovering Social and Aesthetic Categories of Avatars: A Bottom-Up Artificial Intelligence Approach Using Image Clustering (CUL, AL, DFH).
- DiGRA-FDG-2016-ZhuKCL #education #game studies #interactive #social
- Using Interactive Social Story Games to Teach Social Skills to Children with Autism (JZ, CK, JC, NL).
- VS-Games-2016-AyedGJAVM #game studies #people
- Fall Prevention Serious Games for Elderly People Using RGBD Devices (IA, AG, AJiC, BMA, JV, PMB), pp. 1–3.
- VS-Games-2016-LopeM #education #game studies #uml
- Using UML to Model Educational Games (RPdL, NMM), pp. 1–4.
- VS-Games-2016-NicolaouLL #artificial reality
- Stroke Event Simulator Using Virtual Reality (PN, ML, FL), pp. 1–2.
- VS-Games-2016-PaliokasS #game studies
- The Use of Serious Games in Museum Visits and Exhibitions: A Systematic Mapping Study (IP, SS), pp. 1–8.
- VS-Games-2016-Piedra-Fernandez #artificial reality #communication #people
- Sign Communication for People with Disabilities Using Kinect Technology at Home (JAPF, JJOC, CBB, LIM), pp. 1–2.
- VS-Games-2016-VosinakisKMS #approach #artificial reality
- A Kinesthetic Approach to Digital Heritage Using Leap Motion: The Cycladic Sculpture Application (SV, PK, DM, ES), pp. 1–8.
- CIKM-2016-0001H #adaptation #interactive #learning #multi #named
- aptMTVL: Nailing Interactions in Multi-Task Multi-View Multi-Label Learning using Adaptive-basis Multilinear Factor Analyzers (XL0, JH), pp. 1171–1180.
- CIKM-2016-AgrawalC #data mining #mining #predict
- A Fatigue Strength Predictor for Steels Using Ensemble Data Mining: Steel Fatigue Strength Predictor (AA, ANC), pp. 2497–2500.
- CIKM-2016-Balaneshinkordan #concept #graph #query
- Sequential Query Expansion using Concept Graph (SB, AK), pp. 155–164.
- CIKM-2016-CheemaKALWCR #analysis #health #monitoring #on the
- On Structural Health Monitoring Using Tensor Analysis and Support Vector Machine with Artificial Negative Data (PC, NLDK, MMA, WL0, YW0, FC0, PR), pp. 1813–1822.
- CIKM-2016-ChenWPT #community #network #performance
- Efficient Computation of Importance Based Communities in Web-Scale Networks Using a Single Machine (SC, RW, DP, AT), pp. 1553–1562.
- CIKM-2016-HanadaPCL #effectiveness #fault #type system
- Effective Spelling Correction for Eye-based Typing using domain-specific Information about Error Distribution (RH, MdGCP, MC, FAL), pp. 1723–1732.
- CIKM-2016-HansenLM #predict #query #web
- Ensemble Learned Vaccination Uptake Prediction using Web Search Queries (NDH, CL, KM), pp. 1953–1956.
- CIKM-2016-JatowtKT #predict #wiki
- Predicting Importance of Historical Persons using Wikipedia (AJ, DK, KT), pp. 1909–1912.
- CIKM-2016-KuziSK #query #word
- Query Expansion Using Word Embeddings (SK, AS, OK), pp. 1929–1932.
- CIKM-2016-LiCL #approximate #graph #query
- Approximating Graph Pattern Queries Using Views (JL, YC0, XL), pp. 449–458.
- CIKM-2016-LiuKL #predict #social #social media
- Collective Traffic Prediction with Partially Observed Traffic History using Location-Based Social Media (XL, XK, YL), pp. 2179–2184.
- CIKM-2016-ManotumruksaMO #modelling #recommendation
- Regularising Factorised Models for Venue Recommendation using Friends and their Comments (JM, CM, IO), pp. 1981–1984.
- CIKM-2016-MartinoBR0M #community #learning
- Learning to Re-Rank Questions in Community Question Answering Using Advanced Features (GDSM, ABC, SR, AU0, AM), pp. 1997–2000.
- CIKM-2016-Najork #email #experience #machine learning
- Using Machine Learning to Improve the Email Experience (MN), p. 891.
- CIKM-2016-RoyGMJ #composition #estimation #feedback #kernel #word
- Word Vector Compositionality based Relevance Feedback using Kernel Density Estimation (DR, DG, MM, GJFJ), pp. 1281–1290.
- CIKM-2016-RuanSXTFLZ #network
- Forecasting Seasonal Time Series Using Weighted Gradient RBF Network based Autoregressive Model (WR, QZS, PX, NKT0, NJGF, XL0, WEZ), pp. 2021–2024.
- CIKM-2016-SinghC #aspect-oriented #query
- Iterative Search using Query Aspects (MS, WBC), pp. 2037–2040.
- CIKM-2016-TongKIKSV
- Deep Match between Geology Reports and Well Logs Using Spatial Information (BT, MK, MI, YK, AS, RV), pp. 1833–1842.
- CIKM-2016-TutekGSMB #concept #detection #knowledge base #ranking
- Detecting and Ranking Conceptual Links between Texts Using a Knowledge Base (MT, GG, JS, NMF, BDB), pp. 2077–2080.
- CIKM-2016-WangJYJM #learning
- Learning to Extract Conditional Knowledge for Question Answering using Dialogue (PW, LJ, JY0, LJ, WYM), pp. 277–286.
- CIKM-2016-WangOWWLPG #concept
- Using Prerequisites to Extract Concept Maps fromTextbooks (SW, AO, ZW0, KW, CL0, BP, CLG), pp. 317–326.
- CIKM-2016-WangWZ #distributed #graph #partial evaluation #performance #query #rdf
- Efficient Distributed Regular Path Queries on RDF Graphs Using Partial Evaluation (XW0, JW, XZ), pp. 1933–1936.
- CIKM-2016-Wu0XTL #named #recommendation #word
- Tag2Word: Using Tags to Generate Words for Content Based Tag Recommendation (YW, YY0, FX0, HT, JL0), pp. 2287–2292.
- CIKM-2016-XuCLMM #personalisation #recommendation #semantics #similarity
- Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling (ZX, CC0, TL, YM, XM), pp. 1921–1924.
- CIKM-2016-YuanGJCYZ #learning #named #ranking
- LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates (FY, GG, JMJ, LC0, HY, WZ0), pp. 227–236.
- CIKM-2016-ZhangDH #ambiguity #case study #classification #online
- Bayesian Non-Exhaustive Classification A Case Study: Online Name Disambiguation using Temporal Record Streams (BZ, MD, MAH), pp. 1341–1350.
- CIKM-2016-ZhangLDCKS #big data #locality #privacy #scalability
- Scalable Local-Recoding Anonymization using Locality Sensitive Hashing for Big Data Privacy Preservation (XZ, CL, WD, JC, KR, ZS), pp. 1793–1802.
- CIKM-2016-ZhengWPYFX #big data #predict
- Urban Traffic Prediction through the Second Use of Inexpensive Big Data from Buildings (ZZ, DW0, JP, YY, CF, LFX), pp. 1363–1372.
- ECIR-2016-0002B #information retrieval
- Diversifying Search Results Using Time - An Information Retrieval Method for Historians (DG0, KB), pp. 789–795.
- ECIR-2016-ArguelloAD #performance #predict #query
- Using Query Performance Predictors to Improve Spoken Queries (JA, SA, FD0), pp. 309–321.
- ECIR-2016-BalikasA #classification #multi
- Multi-label, Multi-class Classification Using Polylingual Embeddings (GB, MRA), pp. 723–728.
- ECIR-2016-WangME #category theory #fine-grained #image #visual notation
- Harvesting Training Images for Fine-Grained Object Categories Using Visual Descriptions (JW, KM, ME), pp. 549–560.
- ICML-2016-AroraMM #learning #multi #optimisation #probability #representation
- Stochastic Optimization for Multiview Representation Learning using Partial Least Squares (RA, PM, TVM), pp. 1786–1794.
- ICML-2016-BuiHHLT #approximate #process
- Deep Gaussian Processes for Regression using Approximate Expectation Propagation (TDB, DHL, JMHL, YL, RET), pp. 1472–1481.
- ICML-2016-GonenOS #sketching
- Solving Ridge Regression using Sketched Preconditioned SVRG (AG, FO, SSS), pp. 1397–1405.
- ICML-2016-GuanRW #learning #markov #multi #performance #process #recognition
- Efficient Multi-Instance Learning for Activity Recognition from Time Series Data Using an Auto-Regressive Hidden Markov Model (XG, RR, WKW), pp. 2330–2339.
- ICML-2016-JasinskaDBPKH #probability
- Extreme F-measure Maximization using Sparse Probability Estimates (KJ, KD, RBF, KP, TK, EH), pp. 1435–1444.
- ICML-2016-JohnsonZ #categorisation
- Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings (RJ, TZ0), pp. 526–534.
- ICML-2016-JunN #multi
- Anytime Exploration for Multi-armed Bandits using Confidence Information (KSJ, RDN), pp. 974–982.
- ICML-2016-LarsenSLW #encoding #metric #similarity
- Autoencoding beyond pixels using a learned similarity metric (ABLL, SKS, HL, OW), pp. 1558–1566.
- ICML-2016-NiuRFH #parametricity #performance
- Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching (MN, SR, MF, DH), pp. 1699–1707.
- ICML-2016-RoychowdhuryKP #monte carlo #robust
- Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics (AR, BK, SP0), pp. 2673–2681.
- ICML-2016-SangnierGR #detection #proximity #reliability #representation
- Early and Reliable Event Detection Using Proximity Space Representation (MS, JG, AR), pp. 2310–2319.
- ICML-2016-SiHD #approximate #performance
- Computationally Efficient Nyström Approximation using Fast Transforms (SS, CJH, ISD), pp. 2655–2663.
- ICML-2016-ZhuQRY #coordination #performance
- Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling (ZAZ, ZQ, PR, YY), pp. 1110–1119.
- ICPR-2016-AhmedCSNN #image #smarttech
- Using fusion of iris code and periocular biometric for matching visible spectrum iris images captured by smart phone cameras (NUA, SC, EHS, AN, IN), pp. 176–180.
- ICPR-2016-Al-DulaimiBTC #automation #geometry #image #segmentation #set
- Automatic segmentation of HEp-2 cell Fluorescence microscope images using level set method via geometric active contours (KAD, JB, ITR, VC), pp. 81–83.
- ICPR-2016-Alonso-Fernandez #multi #recognition
- Compact multi-scale periocular recognition using SAFE features (FAF, AM, JB), pp. 1455–1460.
- ICPR-2016-AntonyMOM #network
- Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks (JA, KM, NEO, KM), pp. 1195–1200.
- ICPR-2016-AydinKAA #automation #predict #random
- Automatic personality prediction from audiovisual data using random forest regression (BA, AAK, OA, LA), pp. 37–42.
- ICPR-2016-BachaAB #probability #recognition #visual notation
- Event recognition in photo albums using probabilistic graphical model and feature relevance (SB, MSA, NB), pp. 2819–2823.
- ICPR-2016-BartoliLSB #estimation #profiling
- User interest profiling using tracking-free coarse gaze estimation (FB, GL, LS, ADB), pp. 1839–1844.
- ICPR-2016-BertoliniOS #difference #identification #multi
- Multi-script writer identification using dissimilarity (DB, LSO, RS), pp. 3025–3030.
- ICPR-2016-BhagavatulaAS #estimation
- Pose estimation using Spectral and Singular Value recomposition (CB, RA, MS), pp. 4095–4100.
- ICPR-2016-Brandtberg #analysis #classification #fourier #fuzzy #multi #order #rank
- Virtual hexagonal and multi-scale operator for fuzzy rank order texture classification using one-dimensional generalised Fourier analysis (TB), pp. 2018–2024.
- ICPR-2016-BrownF #detection #smarttech
- Enhanced face detection using body part detections for wearable cameras (LMB, QF), pp. 715–720.
- ICPR-2016-BSSH #approach #classification #network
- HEp-2 cell classification using artificial neural network approach (DB, KS, NH), pp. 84–89.
- ICPR-2016-BullingerBWA #bound #generative #re-engineering #video
- Moving object reconstruction in monocular video data using boundary generation (SB, CB, SW, MA), pp. 240–246.
- ICPR-2016-CamgozHKB #3d #gesture #independence #network #recognition
- Using Convolutional 3D Neural Networks for User-independent continuous gesture recognition (NCC, SH, OK, RB), pp. 49–54.
- ICPR-2016-CarbonneauGG #identification #learning #multi #random
- Witness identification in multiple instance learning using random subspaces (MAC, EG, GG), pp. 3639–3644.
- ICPR-2016-ChakrabortyPK #information management #recognition #speech
- Spontaneous speech emotion recognition using prior knowledge (RC, MP, SKK), pp. 2866–2871.
- ICPR-2016-ChowdhuryBMKS #image #network #performance #retrieval
- An efficient radiographic Image Retrieval system using Convolutional Neural Network (MC, SRB, RM, MKK, ÖS), pp. 3134–3139.
- ICPR-2016-Chun #adaptation #authentication
- Small scale single pulse ECG-based authentication using GLRT that considers T wave shift and adaptive template update with prior information (SYC), pp. 3043–3048.
- ICPR-2016-DaiDCLY #multi #rank #representation #segmentation
- Object segmentation using low-rank representation with multiple block-diagonal priors (LD, JD, JC, JL0, JY0), pp. 1959–1964.
- ICPR-2016-DaoodRB #classification #multi #recognition
- Pollen recognition using a multi-layer hierarchical classifier (AD, ER, MB), pp. 3091–3096.
- ICPR-2016-DutaNAIS #recognition
- Boosting VLAD with double assignment using deep features for action recognition in videos (ICD, TAN0, KA, BI, NS), pp. 2210–2215.
- ICPR-2016-EichhardtH
- Improvement of camera calibration using surface normals (IE, LH), pp. 3745–3750.
- ICPR-2016-ElTantawyS #matrix #novel #physics
- A novel method for segmenting moving objects in aerial imagery using matrix recovery and physical spring model (AE, MSS), pp. 3898–3903.
- ICPR-2016-EumD #evaluation #multi
- Content selection using frontalness evaluation of multiple frames (SE, DSD), pp. 3404–3409.
- ICPR-2016-FariaCLI #dependence #recognition
- Information fusion for cocaine dependence recognition using fMRI (FAF, FAMC, CsRL, JSI), pp. 1107–1112.
- ICPR-2016-FengLL #effectiveness #learning
- Learning effective Gait features using LSTM (YF0, YL, JL), pp. 325–330.
- ICPR-2016-FoareLT16a #calculus #functional #image #segmentation
- Image restoration and segmentation using the Ambrosio-Tortorelli functional and Discrete Calculus (MF, JOL, HT), pp. 1418–1423.
- ICPR-2016-GaoCZFZ #image #segmentation
- Texture image segmentation using fused features and active contour (MG, HC, SZ, BF0, LZ), pp. 2036–2041.
- ICPR-2016-GaoYGC #approach #constraints #network
- Bayesian approach to learn Bayesian networks using data and constraints (XGG, YY, ZgG, DQC0), pp. 3667–3672.
- ICPR-2016-GhoraiMC #image #kernel #statistics
- Patch sparsity based image inpainting using local patch statistics and steering kernel descriptor (MG, SM, BC), pp. 781–786.
- ICPR-2016-GiraudTP #linear #named
- SCALP: Superpixels with Contour Adherence using Linear Path (RG, VTT, NP), pp. 2374–2379.
- ICPR-2016-GrimmMBS #classification
- Sleep position classification from a depth camera using Bed Aligned Maps (TG, MM, AB, RS), pp. 319–324.
- ICPR-2016-GuoDFS #detection #robust
- A robust UAV landing site detection system using mid-level discriminative patches (XG, SD, CF, SS), pp. 1659–1664.
- ICPR-2016-HafemannSO #verification
- Analyzing features learned for Offline Signature Verification using Deep CNNs (LGH, RS, LSO), pp. 2989–2994.
- ICPR-2016-HajduHBLEHT #algorithm #approximate #grid #network
- Measuring regularity of network patterns by grid approximations using the LLL algorithm (AH, BH, RB, IL, GE, LH, RT), pp. 1524–1529.
- ICPR-2016-HasegawaH #classification #image #named #network
- PLSNet: A simple network using Partial Least Squares regression for image classification (RH, KH), pp. 1601–1606.
- ICPR-2016-HsuCH #representation #verification
- Object verification in two views using Sparse representation (SCH, ICC, CLH), pp. 504–509.
- ICPR-2016-HuangY #3d #network
- Point cloud labeling using 3D Convolutional Neural Network (JH0, SY), pp. 2670–2675.
- ICPR-2016-ItoA #authentication
- A score calculation method using positional information of feature points for biometric authentication (KI, TA), pp. 3049–3054.
- ICPR-2016-JafariKNSSWN #image #learning #segmentation
- Skin lesion segmentation in clinical images using deep learning (MHJ, NK, ENE, SS, SMRS, KRW, KN), pp. 337–342.
- ICPR-2016-JhuangLT #3d #network #verification
- Face verification with three-dimensional point cloud by using deep belief networks (DHJ, DTL, CHT), pp. 1430–1435.
- ICPR-2016-JiaoZ #learning #multi #taxonomy
- Multiple Instance Dictionary Learning using Functions of Multiple Instances (CJ, AZ), pp. 2688–2693.
- ICPR-2016-JohnKGNMI #learning #modelling #performance #segmentation
- Fast road scene segmentation using deep learning and scene-based models (VJ, KK, CG, HTN, SM, KI), pp. 3763–3768.
- ICPR-2016-JoyR0V #big data #optimisation
- Hyperparameter tuning for big data using Bayesian optimisation (TTJ, SR, SG0, SV), pp. 2574–2579.
- ICPR-2016-KalraSRT #learning #network
- Learning opposites using neural networks (SK, AS, SR, HRT), pp. 1213–1218.
- ICPR-2016-Kamkar0LPV #graph #predict
- Stable clinical prediction using graph support vector machines (IK, SG0, CL0, DQP, SV), pp. 3332–3337.
- ICPR-2016-KhanH #adaptation #learning #polynomial
- Adapting instance weights for unsupervised domain adaptation using quadratic mutual information and subspace learning (MNAK, DRH), pp. 1560–1565.
- ICPR-2016-KilicarslanZ #video
- Bridge motion to collision alarming using driving video (MK, JYZ), pp. 1870–1875.
- ICPR-2016-KimP #approach #detection #network
- A shape preserving approach for salient object detection using convolutional neural networks (JK, VP), pp. 609–614.
- ICPR-2016-KimP16a #network
- Discovering characteristic landmarks on ancient coins using convolutional networks (JK, VP), pp. 1595–1600.
- ICPR-2016-KimV #classification #semantics
- Deep Action Unit classification using a binned intensity loss and semantic context model (EK, SV), pp. 4136–4141.
- ICPR-2016-KondratevS #automation #constraints #detection #geometry #image
- Automatic detection of laser-induced structures in live cell fluorescent microscopy images using snakes with geometric constraints (AYK, DVS), pp. 331–336.
- ICPR-2016-LeiT #modelling
- Modeling human-skeleton motion patterns using conditional deep Boltzmann machine (PL, ST), pp. 1845–1850.
- ICPR-2016-Lezoray #image
- High dynamic range image processing using manifold-based ordering (OL), pp. 289–294.
- ICPR-2016-LiaoLL #classification #multi #network #robust
- Skin disease classification versus skin lesion characterization: Achieving robust diagnosis using multi-label deep neural networks (HL, YL, JL), pp. 355–360.
- ICPR-2016-LiuHWLL #image #performance #retrieval #segmentation
- Efficient segmentation for Region-based Image Retrieval using Edge Integrated Minimum Spanning Tree (YL0, LH0, SW, XL, BL), pp. 1929–1934.
- ICPR-2016-LuoGPWY #locality #mobile #multi
- Accurate localization for mobile device using a multi-planar city model (YL, TG, HP, YW, JY), pp. 3733–3738.
- ICPR-2016-MarronePFPSS #fuzzy #segmentation
- Breast segmentation using Fuzzy C-Means and anatomical priors in DCE-MRI (SM0, GP, RF, AP, MS, CS), pp. 1472–1477.
- ICPR-2016-Martinez-DiazCH #encoding #performance #recognition #video
- Efficient video face recognition by using Fisher Vector encoding of binary features (YMD, LC, NH, HMV, LES), pp. 1436–1441.
- ICPR-2016-MatsukawaS #identification
- Person re-identification using CNN features learned from combination of attributes (TM, ES), pp. 2428–2433.
- ICPR-2016-MatsuzakiUSS #2d #3d #constraints #geometry #retrieval #verification
- Geometric verification using semi-2D constraints for 3D object retrieval (KM, YU, SS, SS), pp. 2338–2343.
- ICPR-2016-MohagheghKSSN #estimation #image
- Single image depth estimation using joint local-global features (HM, NK, SMRS, SS, KN), pp. 727–732.
- ICPR-2016-MollerNN16a #clustering #detection #image
- Change detection in marine observatory image streams using Bi-Domain Feature Clustering (TM, IN, TWN), pp. 793–798.
- ICPR-2016-MontenegroA #artificial reality #estimation #human-computer
- Gaze estimation using EEG signals for HCI in augmented and virtual reality headsets (JMFM, VA), pp. 1159–1164.
- ICPR-2016-NahaW16a #learning #segmentation
- Object figure-ground segmentation using zero-shot learning (SN, YW0), pp. 2842–2847.
- ICPR-2016-NairKNG #documentation #network #segmentation
- Segmentation of highly unstructured handwritten documents using a neural network technique (RRN, BUK, IN, VG), pp. 1291–1296.
- ICPR-2016-Nakazawa #image #random
- Noise stable image registration using RANdom RESAmple Consensus (AN), pp. 853–858.
- ICPR-2016-NaminAP #2d #3d #higher-order #segmentation #semantics
- 2D-3D semantic segmentation using cardinality as higher-order loss (SRN, JMA, LP), pp. 3775–3780.
- ICPR-2016-Nguyen #automation #generative #image
- Automatic generation of a realistic looking single image stereogram using stereo vision (MN), pp. 3826–3831.
- ICPR-2016-NishiyamaNYYIS #identification #physics
- Person re-identification using co-occurrence attributes of physical and adhered human characteristics (MN, SN, TY, HY, YI, KS), pp. 2085–2090.
- ICPR-2016-OnZEB #multi #pattern matching #pattern recognition #recognition
- Spatio-temporal pattern recognition of dendritic spines and protein dynamics using live multichannel fluorescence microscopy (VO, AZ, IE, BB), pp. 2042–2047.
- ICPR-2016-OrriteRM #distance #learning #process #sequence
- One-shot learning of temporal sequences using a distance dependent Chinese Restaurant Process (CO, MR, CM), pp. 2694–2699.
- ICPR-2016-OrueG #graph #process #recognition
- Face recognition using activities of directed graphs in spatial pyramid (JPMO, WNG), pp. 3162–3167.
- ICPR-2016-Oskarsson
- Characterizing the structure tensor using gamma distributions (MO), pp. 763–768.
- ICPR-2016-PalaniappanPAVF #detection
- Moving object detection for vehicle tracking in Wide Area Motion Imagery using 4D filtering (KP, MP, HA, RV, JF, FB, AB, SS, EB, RMR, GS), pp. 2830–2835.
- ICPR-2016-PalCGCC #learning #multi
- Severity grading of psoriatic plaques using deep CNN based multi-task learning (AP, AC, UG, AC, RC), pp. 1478–1483.
- ICPR-2016-PengRP #learning #network #recognition
- Learning face recognition from limited training data using deep neural networks (XP, NKR, SP), pp. 1442–1447.
- ICPR-2016-Ponce-Hinestroza #adaptation
- Using a MRF-BP model with color adaptive training for underwater color restoration (ANPH, LATM, PDJ), pp. 787–792.
- ICPR-2016-PrasathKOGHSP #classification #random #segmentation
- HEp-2 cell classification and segmentation using motif texture patterns and spatial features with random forests (VBSP, YMK, ZAO, JBG, AH, GS, KP), pp. 90–95.
- ICPR-2016-QinJYW #image #recognition
- Building facade recognition from aerial images using Delaunay Triangulation induced feature perceptual grouping (XQ, MJ, XY, JW0), pp. 3368–3373.
- ICPR-2016-QuachtranHS #detection #learning
- Detection of Intracranial Hypertension using Deep Learning (BQ, RBH, FS), pp. 2491–2496.
- ICPR-2016-QuWL #recognition #representation
- In-air handwritten Chinese character recognition using discriminative projection based on locality-sensitive sparse representation (XQ, WW, KL), pp. 1137–1140.
- ICPR-2016-RaiNCD #clustering #graph #multi
- Partial Multi-View Clustering using Graph Regularized NMF (NR, SN, SC, OD), pp. 2192–2197.
- ICPR-2016-RaytchevKTK #kernel #recognition #representation
- Higher-level representation of local spatio-temporal features for human action recognition using Subspace Matching Kernels (BR, HK, TT, KK), pp. 3862–3867.
- ICPR-2016-Robles-KellyW #graph #image
- Semi-supervised image labelling using barycentric graph embeddings (ARK, RW), pp. 1518–1523.
- ICPR-2016-Rowekamp #performance
- Fast thresholding of high dimensional Euclidean distances using binary squaring (JHR), pp. 3103–3108.
- ICPR-2016-SagawaSHOKF #automation #feature model #robust
- Automatic feature extraction using CNN for robust active one-shot scanning (RS, YS, TH, SO, HK, RF), pp. 234–239.
- ICPR-2016-SahooA0 #approach #automation #clustering #generative #multi
- Automatic generation of biclusters from gene expression data using multi-objective simulated annealing approach (PS, SA, SS0), pp. 2174–2179.
- ICPR-2016-SaikiaSSKG #analysis #kernel #learning #multi
- Multiple kernel learning using data envelopment analysis and feature vector selection and projection (GS, SS, VVS, RDK, PG), pp. 520–524.
- ICPR-2016-SerinoB #3d
- Using local convexities as anchor points for 3D curve skeletonization (LS, GSdB), pp. 2854–2859.
- ICPR-2016-ShigetaMKSTMI #segmentation
- A bone marrow cavity segmentation method using wavelet-based texture feature (HS, TM, JK, SS, HT, HM, MI), pp. 2133–2138.
- ICPR-2016-ShiWXW #adaptation #image
- OTSU guided adaptive binarization of CAPTCHA image using gamma correction (CS, YW, BX, CW), pp. 3962–3967.
- ICPR-2016-SidibeRM #detection #multi #on the
- On spatio-temporal saliency detection in videos using multilinear PCA (DS, MR, FM), pp. 1876–1880.
- ICPR-2016-SuCHH #detection #image #modelling #recognition #symmetry
- Moment-based symmetry detection for scene modeling and recognition using RGB-D images (JYS, SCC, JWH, THH), pp. 3621–3626.
- ICPR-2016-SunBTTH #detection #learning #locality
- Tattoo detection and localization using region-based deep learning (ZS, JB, PT, MT, AH), pp. 3055–3060.
- ICPR-2016-SunHL #detection #image
- Context based face spoofing detection using active near-infrared images (XS0, LH0, CL), pp. 4262–4267.
- ICPR-2016-TakabeTKSMNY #consistency #detection
- Moving object detection from a point cloud using photometric and depth consistencies (AT, HT, NK, TS, TM, SN, NY), pp. 561–566.
- ICPR-2016-TakadaHJ
- Human tracking in crowded scenes using target information at previous frames (HT, KH, PJ), pp. 1809–1814.
- ICPR-2016-TakahashiIKOM #multi #robust
- Robust volleyball tracking system using multi-view cameras (MT, KI, MK, HO, TM), pp. 2740–2745.
- ICPR-2016-TakezawaHT #detection #documentation #image
- Camera-captured document image perspective distortion correction using vanishing point detection based on Radon transform (YT, MH, ST), pp. 3968–3974.
- ICPR-2016-TianMO #detection #embedded #low cost #recognition
- Spoofing detection for embedded face recognition system using a low cost stereo camera (GT, TM, YO), pp. 1017–1022.
- ICPR-2016-TizhooshMZD #image #retrieval
- Barcodes for medical image retrieval using autoencoded Radon transform (HRT, CM, SZ, SD), pp. 3150–3155.
- ICPR-2016-ToyamaMS #clustering #performance
- Fast template matching using Brick Partitioning and initial threshold (FT, HM, KS), pp. 687–691.
- ICPR-2016-VinhEPBLR #modelling #random #robust
- Training robust models using Random Projection (XVN, SME, SP, JB0, CL, KR), pp. 531–536.
- ICPR-2016-WangLLGTO #gesture #network #recognition #scalability
- Large-scale Isolated Gesture Recognition using Convolutional Neural Networks (PW, WL, SL, ZG, CT, PO), pp. 7–12.
- ICPR-2016-WangLLZGO #gesture #network #recognition #scalability
- Large-scale Continuous Gesture Recognition Using Convolutional Neural Networks (PW, WL, SL, YZ, ZG, PO), pp. 13–18.
- ICPR-2016-WangWH #analysis #network
- Network entropy analysis using the Maxwell-Boltzmann partition function (JW, RCW0, ERH), pp. 1321–1326.
- ICPR-2016-WarisIG
- Object proposals using CNN-based edge filtering (MAW, AI, MG), pp. 627–632.
- ICPR-2016-Williams #classification #network
- Underwater target classification in synthetic aperture sonar imagery using deep convolutional neural networks (DPW), pp. 2497–2502.
- ICPR-2016-WuLZN #modelling #re-engineering
- Model-based face reconstruction using SIFT flow registration and spherical harmonics (FW, SL, TZ, KNN), pp. 1774–1779.
- ICPR-2016-XuLHWLWHC #3d #image #multi #retrieval #word
- Bag of temporal co-occurrence words for retrieval of focal liver lesions using 3D multiphase contrast-enhanced CT images (YX, LL, HH, DW, YL, JW0, XHH, YWC), pp. 2282–2287.
- ICPR-2016-YamashitaFYF #detection #multi #network
- Pedestrian and part position detection using a regression-based multiple task deep convolutional neural network (TY, HF, YY, HF), pp. 3500–3505.
- ICPR-2016-YangJNL #network #normalisation #online #recognition
- Rotation-free online handwritten character recognition using dyadic path signature features, hanging normalization, and deep neural network (WY, LJ, HN, TL), pp. 4083–4088.
- ICPR-2016-YangL #learning #nondeterminism
- Active learning using uncertainty information (YY, ML), pp. 2646–2651.
- ICPR-2016-YB #3d #optimisation #video
- Rate distortion optimization using SSIM for 3D video coding (HY, PKB), pp. 1261–1266.
- ICPR-2016-YeWH #generative #graph
- Analyzing graph time series using a generative model (CY, RCW0, ERH), pp. 3338–3343.
- ICPR-2016-YildizU #classification #incremental #order
- Incremental construction of rule ensembles using classifiers produced by different class orderings (OTY, AU), pp. 492–497.
- ICPR-2016-YodaNTKYK #image #multi
- Dynamic photometric stereo method using multi-tap CMOS image sensor (TY, HN, RiT, KK, KY, SK), pp. 2356–2361.
- ICPR-2016-YuLC #multi
- Recognizing text in historical maps using maps from multiple time periods (RY, ZL, YYC), pp. 3993–3998.
- ICPR-2016-YuWSH #invariant #recognition
- View invariant gait recognition using only one uniform model (SY, QW, LS, YH), pp. 889–894.
- ICPR-2016-ZemeneTPP #clustering #detection #set
- Simultaneous clustering and outlier detection using dominant sets (EZ, YTT, AP0, MP), pp. 2325–2330.
- ICPR-2016-ZhangGSSL #robust
- Robust tensor factorization using maximum correntropy criterion (MZ, YG, CS, JLS, JL), pp. 4184–4189.
- ICPR-2016-ZhangLQ #network
- Wake-up-word spotting using end-to-end deep neural network system (SZ, WL, YQ0), pp. 2878–2883.
- ICPR-2016-ZhangWY #correlation #image
- Theoretical criterion for image matching using GPT correlation (SZ, TW, YY), pp. 555–560.
- ICPR-2016-ZhaoIBJ #fault #predict
- Wind turbine fault prediction using soft label SVM (RZ, MRAI, KPB, QJ), pp. 3192–3197.
- ICPR-2016-ZhaoMFQH #performance #predict
- Fast motion deblurring using gyroscopes and strong edge prediction (JZ, JM, BF, SQ, FH), pp. 739–744.
- ICPR-2016-ZhengCZZL #independence #network
- Text-independent voice conversion using deep neural network based phonetic level features (HZ, WC, TZ, SZ, ML0), pp. 2872–2877.
- ICPR-2016-ZhengLZW #image #multi
- Multi-focus image fusion using quaternion wavelet transform (XNZ, XL, ZZ, XJW), pp. 883–888.
- ICPR-2016-ZhugeHNY #clustering #feature model #graph
- Unsupervised feature extraction using a learned graph with clustering structure (WZ, CH, FN, DY), pp. 3597–3602.
- ICPR-2016-ZhuZMSSS #3d #gesture #network #recognition #scalability
- Large-scale Isolated Gesture Recognition using pyramidal 3D convolutional networks (GZ, LZ0, LM, JS, JS, PS), pp. 19–24.
- KDD-2016-AgostaGHIKZ #clustering #data analysis #scalability
- Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters (JMA, DG, RH, MI, SK, MZ), p. 2115.
- KDD-2016-BrooksKG #data-driven #predict #ranking
- Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights (JB, MK, JVG), pp. 49–55.
- KDD-2016-ChakrabortyVJS #predict
- Predicting Socio-Economic Indicators using News Events (SC, AV, SJ, LS), pp. 1455–1464.
- KDD-2016-ChenLHYGG
- City-Scale Map Creation and Updating using GPS Collections (CC0, CL, QH, QY0, DG, LJG), pp. 1465–1474.
- KDD-2016-HaarenSDF #machine learning
- Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques (JVH, HBS, JD, PF), pp. 627–634.
- KDD-2016-HaPK #categorisation #e-commerce #multi #network #scalability
- Large-Scale Item Categorization in e-Commerce Using Multiple Recurrent Neural Networks (JH, HP, JK), pp. 107–115.
- KDD-2016-HuoNH #effectiveness #learning #metric #robust
- Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm (ZH, FN, HH), pp. 1605–1614.
- KDD-2016-KuangTCPSP #self
- Computational Drug Repositioning Using Continuous Self-Controlled Case Series (ZK, JAT, MC, PLP, RMS, DP), pp. 491–500.
- KDD-2016-NandiMADB #control flow #detection #execution #graph #mining
- Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs (AN, AM, SA, GBD, SB), pp. 215–224.
- KDD-2016-ReisFMB #detection #incremental #online #performance
- Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test (DMdR, PAF, SM, GEAPAB), pp. 1545–1554.
- KDD-2016-SinghSA #independence #machine learning
- Question Independent Grading using Machine Learning: The Case of Computer Program Grading (GS, SS, VA), pp. 263–272.
- KDD-2016-TaghaviLK #machine learning #memory management #recommendation
- Compute Job Memory Recommender System Using Machine Learning (TT, ML, YK), pp. 609–616.
- KDD-2016-TingZCZZ #difference
- Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure (KMT, YZ, MJC, YZ, ZHZ), pp. 1205–1214.
- KDD-2016-YinW #algorithm #clustering #online
- A Text Clustering Algorithm Using an Online Clustering Scheme for Initialization (JY, JW), pp. 1995–2004.
- KDD-2016-ZhangZYZHH #modelling #named #social #social media
- GMove: Group-Level Mobility Modeling Using Geo-Tagged Social Media (CZ0, KZ, QY0, LZ, TH, JH0), pp. 1305–1314.
- KDD-2016-ZhaoATBDBKD #approach #detection #parametricity #strict
- A Non-parametric Approach to Detect Epileptogenic Lesions using Restricted Boltzmann Machines (YZ, BA, TT, KEB, JGD, CEB, RK, OD), pp. 373–382.
- BX-2016-SemerathDHV #co-evolution #logic #modelling #satisfiability #synthesis
- Change Propagation of View Models by Logic Synthesis using SAT solvers (OS, CD, ÁH0, DV), pp. 40–44.
- ECMFA-2016-HeimNRW #composition #static typing #type safety
- Compositional Language Engineering Using Generated, Extensible, Static Type-Safe Visitors (RH, PMSN, BR, AW), pp. 67–82.
- ECMFA-2016-KessentiniSW #approach #automation #co-evolution #metamodelling #multi #optimisation
- Automated Metamodel/Model Co-evolution Using a Multi-objective Optimization Approach (WK, HAS, MW), pp. 138–155.
- ICMT-2016-MooijJEJR #industrial #open source #parsing
- Industrial Software Rejuvenation Using Open-Source Parsers (AJM, MMJ, GE, PJ, AR), pp. 157–172.
- ICMT-2016-RoccoRPCLG #atl #collaboration #framework #modelling #platform
- Using ATL Transformation Services in the MDEForge Collaborative Modeling Platform (JDR, DDR, AP, JSC, JdL, EG), pp. 70–78.
- ICMT-2016-SalayZC #reuse
- Correct Reuse of Transformations is Hard to Guarantee (RS, SZ, MC), pp. 107–122.
- MoDELS-2016-BergmannDRV #bidirectional #collaboration #data access #modelling
- Query-based access control for secure collaborative modeling using bidirectional transformations (GB, CD, IR, DV), pp. 351–361.
- MoDELS-2016-Blache #bound #c #development #embedded #modelling #safety
- Handling index-out-of-bounds in safety-critical embedded C code using model-based development (GB), pp. 143–149.
- MoDELS-2016-GolraBDGG #agile #modelling
- Using free modeling as an agile method for developing domain specific modeling languages (FRG, AB, FD, SG, CG), pp. 24–34.
- MoDELS-2016-KalenkovaALR #mining #modelling #process
- Process mining using BPMN: relating event logs and process models (AAK, WMPvdA, IAL, VAR), p. 123.
- MoDELS-2016-SzvetitsZ #comprehension #design #empirical #modelling #runtime
- Controlled experiment on the comprehension of runtime phenomena using models created at design time (MS, UZ), pp. 151–161.
Onward-2016-MarterBLH #identifier #lightweight #programming #readability #similarity #source code- Lightweight programming experiments without programmers and programs: an example study on the effect of similarity and number of object identifiers on the readability of source code using natural texts (TM, PB, PL, SH), pp. 1–14.
- OOPSLA-2016-GollamudiC #automation #policy #security
- Automatic enforcement of expressive security policies using enclaves (AG, SC), pp. 494–513.
- OOPSLA-2016-Itzhaky0SYLLC #algorithm #divide and conquer #programming
- Deriving divide-and-conquer dynamic programming algorithms using solver-aided transformations (SI, RS0, ASL, KY, YL, CEL, RAC), pp. 145–164.
- OOPSLA-2016-SteimannHU #attribute grammar #constraints #source code
- Computing repair alternatives for malformed programs using constraint attribute grammars (FS, JH, BU), pp. 711–730.
- OOPSLA-2016-WangGS #named #spreadsheet
- FIDEX: filtering spreadsheet data using examples (XW0, SG, RS), pp. 195–213.
- AdaEurope-2016-LaaliLHSS #detection #fault #online #testing
- Test Case Prioritization Using Online Fault Detection Information (ML, HL, MH, MS, HWS), pp. 78–93.
- AdaEurope-2016-MohaqeqiAY #analysis #data flow #graph #modelling #realtime
- Modeling and Analysis of Data Flow Graphs Using the Digraph Real-Time Task Model (MM, JA, WY0), pp. 15–29.
- AdaEurope-2016-Wittiger #csp
- Eliminating Data Race Warnings Using CSP (MW), pp. 30–43.
- LOPSTR-2016-AngelisFMPP #horn clause #process #verification
- Verification of Time-Aware Business Processes Using Constrained Horn Clauses (EDA, FF, MCM, AP, MP), pp. 38–55.
- PADL-2016-CaretteS #algebra #probability #source code
- Simplifying Probabilistic Programs Using Computer Algebra (JC, CcS), pp. 135–152.
- PADL-2016-JelinekB #array #constraints #logic programming
- Using Constraint Logic Programming to Schedule Solar Array Operations on the International Space Station (JJ, RB), pp. 3–12.
- PLDI-2016-KimJJKL #distributed #framework #replication
- A distributed OpenCL framework using redundant computation and data replication (JK, GJ, JJ, JK, JL), pp. 553–569.
- PLDI-2016-LaurenzanoHSMMT #approximate #latency
- Input responsiveness: using canary inputs to dynamically steer approximation (MAL, PH, MS, SAM, JM, LT), pp. 161–176.
- POPL-2016-0001NMR #invariant #learning
- Learning invariants using decision trees and implication counterexamples (PG0, DN, PM, DR), pp. 499–512.
- POPL-2016-AltenkirchK #induction #type system
- Type theory in type theory using quotient inductive types (TA, AK), pp. 18–29.
- POPL-2016-KatzEY #modelling #predict
- Estimating types in binaries using predictive modeling (OK, REY, EY), pp. 313–326.
- POPL-2016-PlotkinBLRV #network #scalability #symmetry #verification
- Scaling network verification using symmetry and surgery (GDP, NB, NPL, AR, GV), pp. 69–83.
- POPL-2016-SinghG #data type #spreadsheet
- Transforming spreadsheet data types using examples (RS, SG), pp. 343–356.
- PPDP-2016-AlbertAG #concurrent #imperative #testing
- Testing of concurrent and imperative software using CLP (EA, PA, MGZ), pp. 1–8.
- SAS-2016-GharatKM #analysis #graph #points-to
- Flow- and Context-Sensitive Points-To Analysis Using Generalized Points-To Graphs (PMG, UPK, AM), pp. 212–236.
- ASE-2016-AbdessalemNBS #multi #network #testing
- Testing advanced driver assistance systems using multi-objective search and neural networks (RBA, SN, LCB, TS), pp. 63–74.
- ASE-2016-AlmhanaMK0 #debugging #multi #recommendation
- Recommending relevant classes for bug reports using multi-objective search (RA, WM, MK, AO), pp. 286–295.
- ASE-2016-AlshanqitiHK #contract #dynamic analysis #reverse engineering #visual notation
- Visual contract extractor: a tool for reverse engineering visual contracts using dynamic analysis (AMA, RH, TK), pp. 816–821.
- ASE-2016-BaekB #android #automation #comparison #modelling #multi #testing #user interface
- Automated model-based Android GUI testing using multi-level GUI comparison criteria (YMB, DHB), pp. 238–249.
- ASE-2016-FengJCF #comprehension #image #multi
- Multi-objective test report prioritization using image understanding (YF, JAJ, ZC, CF), pp. 202–213.
- ASE-2016-MoonenABR #guidelines #mining #recommendation
- Practical guidelines for change recommendation using association rule mining (LM, SDA, DB, TR), pp. 732–743.
- ASE-2016-Mougouei #dependence #graph #integer #programming #requirements
- Factoring requirement dependencies in software requirement selection using graphs and integer programming (DM), pp. 884–887.
- ASE-2016-Nishi #bound #model checking #programming #towards
- Towards bounded model checking using nonlinear programming solver (MN), pp. 560–565.
- ASE-2016-PatrickCSG #automation #generative #image
- Automatic test image generation using procedural noise (MP, MDC, ROJHS, CAG), pp. 654–659.
- ASE-2016-PeldszusKLS #design #detection #evolution #incremental #multi #object-oriented #pattern matching #source code
- Continuous detection of design flaws in evolving object-oriented programs using incremental multi-pattern matching (SP, GK, ML, SS), pp. 578–589.
- ASE-2016-RahmanR #automation #concept #crowdsourcing #named #query
- QUICKAR: automatic query reformulation for concept location using crowdsourced knowledge (MMR, CKR), pp. 220–225.
- ASE-2016-YamadaBAKC #combinator #generative #satisfiability #testing
- Greedy combinatorial test case generation using unsatisfiable cores (AY, AB, CA, TK, EHC), pp. 614–624.
FSE-2016-Alexandru #network #synthesis- Guided code synthesis using deep neural networks (CVA), pp. 1068–1070.
- FSE-2016-Hammoudi #testing #tool support #web
- Regression testing of web applications using Record/Replay tools (MH), pp. 1079–1081.
- FSE-2016-Luo16a #automation #performance #profiling #testing
- Automatic performance testing using input-sensitive profiling (QL), pp. 1139–1141.
- FSE-2016-NguyenHCNMRND #api #fine-grained #learning #recommendation #statistics
- API code recommendation using statistical learning from fine-grained changes (ATN0, MH, MC, HAN, LM, ER, TNN, DD), pp. 511–522.
- FSE-2016-NiuWG #requirements #traceability
- Gray links in the use of requirements traceability (NN, WW0, AG), pp. 384–395.
- FSE-2016-Rolim #automation
- Automating repetitive code changes using examples (RR), pp. 1063–1065.
- ICSE-2016-BersaniBGKP #performance #pipes and filters #scalability
- Efficient large-scale trace checking using mapreduce (MMB, DB, CG, SK, PSP), pp. 888–898.
- ICSE-2016-CheungCLX #automation #clustering #detection #named #smell #spreadsheet
- CUSTODES: automatic spreadsheet cell clustering and smell detection using strong and weak features (SCC, WC, YL, CX0), pp. 464–475.
- ICSE-2016-DesaiGHJKMRR #natural language #synthesis
- Program synthesis using natural language (AD, SG, VH, NJ, AK, MM, SR, SR), pp. 345–356.
- ICSE-2016-MullerF #metric #online #predict #quality
- Using (bio)metrics to predict code quality online (SCM, TF0), pp. 452–463.
- ICSE-2016-NearJ #data access #debugging #security #web
- Finding security bugs in web applications using a catalog of access control patterns (JPN, DJ0), pp. 947–958.
- ICSE-2016-Rubio-Gonzalez0 #analysis #float #precise
- Floating-point precision tuning using blame analysis (CRG, CN0, BM, KS, JD, WK, CI, WL, DHB, DH), pp. 1074–1085.
- ICSE-2016-SuRT #evaluation #model checking #parametricity #reliability #runtime
- Reliability of Run-Time Quality-of-Service evaluation using parametric model checking (GS, DSR, GT), pp. 73–84.
- ICSE-2016-ZhangZZH #classification #fault #predict
- Cross-project defect prediction using a connectivity-based unsupervised classifier (FZ0, QZ, YZ0, AEH), pp. 309–320.
- GPCE-2016-Al-HajjajiKTLS #incremental #named #performance #product line #testing
- IncLing: efficient product-line testing using incremental pairwise sampling (MAH, SK, TT, ML, GS), pp. 144–155.
- SLE-2016-AmorimEWV #code completion
- Principled syntactic code completion using placeholders (LEdSA, SE, GW, EV), pp. 163–175.
- SLE-2016-VoelterSLKEB #consistency #development #editing #performance #projectional
- Efficient development of consistent projectional editors using grammar cells (MV, TS, SL, BK, SE, TB), pp. 28–40.
- ASPLOS-2016-BrownNE #how #order #static analysis
- How to Build Static Checking Systems Using Orders of Magnitude Less Code (FB, AN, DRE), pp. 143–157.
- ASPLOS-2016-GuoSCM #approximate #image #memory management
- High-Density Image Storage Using Approximate Memory Cells (QG, KS, LC, HSM), pp. 413–426.
- ASPLOS-2016-ZhangLJ #concurrent #detection #hardware #memory management #named #performance #transaction
- TxRace: Efficient Data Race Detection Using Commodity Hardware Transactional Memory (TZ, DL, CJ), pp. 159–173.
- CASE-2016-AndreJT #assembly #modelling #reliability
- Reliable robot assembly using haptic rendering models in combination with particle filters (RA, MJ, UT), pp. 1134–1139.
- CASE-2016-ChengZWCJL #case study #data mining #energy #fault #mining
- Case studies of fault diagnosis and energy saving in buildings using data mining techniques (ZC, QZ, FW, ZC, YJ, YL), pp. 646–651.
- CASE-2016-DuH #petri net #robust
- Robust control of Backward Conflict Free Systems with Resources using Petri nets (ND, HH), pp. 1034–1041.
- CASE-2016-GargSKJMMG #adaptation #automation #locality #process
- Tumor localization using automated palpation with Gaussian Process Adaptive Sampling (AG, SS, RK, YJ, SM, LM, KG), pp. 194–200.
- CASE-2016-HsuYL #analysis #process
- Effect analysis and optimal combination of cutting conditions on the cutting torque of tapping processes using Taguchi methods (CCH, SSY, JIL), pp. 1215–1218.
- CASE-2016-IrieST #dependence
- Target-less camera-LiDAR extrinsic calibration using a bagged dependence estimator (KI, MS, MT), pp. 1340–1347.
- CASE-2016-LaskeyLCGHPDG #learning
- Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations (ML, JL, CC, DVG, WYSH, FTP, ADD, KG), pp. 827–834.
- CASE-2016-LiSXSL #framework #hybrid #low cost
- A hybrid model and kinematic-free control framework for a low-cost deformable manipulator using in home service (GL, LS0, SX, DS, JL), pp. 1002–1007.
- CASE-2016-LiuT #distributed #hybrid #multi #network
- Distributed vision network for multiple target tracking using a dynamic hybrid consensus filter (GL, GT), pp. 805–808.
- CASE-2016-MahadevKRFB #grid
- Collecting a swarm in a grid environment using shared, global inputs (AVM, DK, JMR, SPF, ATB), pp. 1231–1236.
- CASE-2016-ShahrokhiB
- Object manipulation and position control using a swarm with global inputs (SS, ATB), pp. 561–566.
- CASE-2016-SrinivasanC #approach #approximate #orthogonal
- Path planning with user route preference - A reward surface approximation approach using orthogonal Legendre polynomials (ARS, SC), pp. 1100–1105.
- CASE-2016-TanCPT #automation #design #diagrams #evaluation #layout
- Automated design evaluation on layout of Piping and Instrumentation Diagram using Histogram of Connectivity (WCT, IMC, SJP, HKT), pp. 1295–1300.
- CASE-2016-TsaiWPXLFZ #behaviour #predict #process #smarttech
- Context-aware activity prediction using human behavior pattern in real smart home environments (MJT, CLW, SKP, YX, TYL, LCF, YCZ), pp. 168–173.
- CASE-2016-WiebeRRV #approach #automation #composition #delivery #fault #generative #injection #simulation #testing
- Automated test suite generation to test modular designed packaging machines using Fault Injection and a simulink-based simulation approach (FW, SR, SR, BVH), pp. 758–765.
- CASE-2016-YangH #distributed #petri net
- Mono-T-semiflow systems with resources and their distributed control using Petri nets (YY, HH), pp. 1042–1048.
- CASE-2016-ZouFP #estimation #metric #network
- Psychoacoustic impacts estimation in manufacturing based on accelerometer measurement using artificial neural networks (MZ, LF, JP), pp. 1203–1208.
- CAV-2016-KafleGM #abstract interpretation #automaton #finite #horn clause #named #verification
- Rahft: A Tool for Verifying Horn Clauses Using Abstract Interpretation and Finite Tree Automata (BK, JPG, JFM), pp. 261–268.
- CAV-2016-MuellerSS #automation #execution #symbolic computation #verification
- Automatic Verification of Iterated Separating Conjunctions Using Symbolic Execution (PM, MS, AJS), pp. 405–425.
- CAV-2016-PernsteinerLTTW #modelling #safety
- Investigating Safety of a Radiotherapy Machine Using System Models with Pluggable Checkers (SP, CL, ET, ZT, XW0, MDE, JJ), pp. 23–41.
- ICST-2016-HuoC
- Interpreting Coverage Information Using Direct and Indirect Coverage (CH, JC), pp. 234–243.
- ICST-2016-MahajanLBH #debugging #visual notation #web
- Using Visual Symptoms for Debugging Presentation Failures in Web Applications (SM, BL, PB, WGJH), pp. 191–201.
- ICST-2016-MarculescuFT #evaluation #search-based #testing
- Using Exploration Focused Techniques to Augment Search-Based Software Testing: An Experimental Evaluation (BM, RF, RT), pp. 69–79.
- ICTSS-2016-EnoiuSCFP #embedded #generative #model checking #testing
- Mutation-Based Test Generation for PLC Embedded Software Using Model Checking (EPE, DS, AC, RF, PP), pp. 155–171.
- ICTSS-2016-PradhanWAYL #industrial #multi #named #testing
- STIPI: Using Search to Prioritize Test Cases Based on Multi-objectives Derived from Industrial Practice (DP, SW0, SA0, TY0, ML), pp. 172–190.
- ICTSS-2016-ReichstallerEKR #learning #testing
- Risk-Based Interoperability Testing Using Reinforcement Learning (AR, BE, AK, WR, MG), pp. 52–69.
- IJCAR-2016-AthanasiouLW #bound #equation #thread #verification
- Unbounded-Thread Program Verification using Thread-State Equations (KA, PL, TW), pp. 516–531.
- IJCAR-2016-DawsonBG #calculus #logic #theorem
- Machine-Checked Interpolation Theorems for Substructural Logics Using Display Calculi (JED, JB, RG), pp. 452–468.
- TAP-2016-ReichlFT #formal method #validation #verification
- Using Formal Methods for Verification and Validation in Railway (KR, TF, PT), pp. 3–13.
- VMCAI-2016-MarechalFKMP #approximate #multi #theorem
- Polyhedral Approximation of Multivariate Polynomials Using Handelman's Theorem (AM, AF, TK0, DM, MP), pp. 166–184.
- CBSE-2015-MouelhiACM #behaviour #component #contract #design #object-oriented
- Object-Oriented Component-Based Design using Behavioral Contracts: Application to Railway Systems (SM, KA, SC, HM), pp. 49–58.
- ECSA-2015-AgrawalP #adaptation #framework #towards #web
- Towards a Framework for Building Adaptive App-Based Web Applications Using Dynamic Appification (AA, TVP), pp. 37–44.
- ECSA-2015-GalsterA #agile #architecture #comprehension #development
- Understanding the Use of Reference Architectures in Agile Software Development Projects (MG, SA), pp. 268–276.
- ECSA-2015-HansenM #automation #community #composition #detection
- (Automated) Software Modularization Using Community Detection (KMH, KM), pp. 95–102.
- ECSA-2015-TahriDP #architecture #deployment #distributed #feature model #modelling #smarttech
- Using Feature Models for Distributed Deployment in Extended Smart Home Architecture (AT, LD, JP), pp. 285–293.
- QoSA-2015-HofigZS #automation #dependence
- Automated Failure Propagation using Inner Port Dependency Traces (KH, MZ, KS), pp. 123–128.
DocEng-2015-FerreiraLCFSR #automation #classification #documentation #summary- Automatic Document Classification using Summarization Strategies (RF, RDL, LdSC, FF, SJS, MR), pp. 69–72.
- DocEng-2015-LesnikovaDE #rdf
- Interlinking English and Chinese RDF Data Using BabelNet (TL, JD, JE), pp. 39–42.
DRR-2015-BideaultMCP #architecture #regular expression #word- Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture (GB, LM, CC, TP).
- DRR-2015-MehriSHGAM #documentation #image #segmentation
- Use of SLIC superpixels for ancient document image enhancement and segmentation (MM, NS, PH, PGK, NEBA, RM), p. 940205.
- DRR-2015-PengCN #approach
- Boost OCR accuracy using iVector based system combination approach (XP, HC, PN).
- DRR-2015-RabaevCEK #documentation #programming
- Aligning transcript of historical documents using dynamic programming (IR, RC, JES, KK).
- DRR-2015-SitaramHPSK #recognition #word
- Offline handwritten word recognition using MQDF-HMMs (RS, MH, AP, DS, SK).
- DRR-2015-StalnakerZ #retrieval
- Math expression retrieval using an inverted index over symbol pairs (DS, RZ), p. 940207.
HT-2015-Bayomi #adaptation #corpus #framework #reuse- A Framework to Provide Customized Reuse of Open Corpus Content for Adaptive Systems (MB), pp. 315–318.
- HT-2015-BlountMW #logic #social #web
- An Investigation into the Use of Logical and Rhetorical Tactics within Eristic Argumentation on the Social Web (TB, DEM, MJW), pp. 195–199.
- JCDL-2015-CuongCKL #documentation #higher-order #information management #performance
- Scholarly Document Information Extraction using Extensible Features for Efficient Higher Order Semi-CRFs (NVC, MKC, MYK, WSL), pp. 61–64.
PODS-2015-CateCST #ontology- High-Level Why-Not Explanations using Ontologies (BtC, CC, ES, WCT), pp. 31–43.
SIGMOD-2015-BarthelsLAK #in memory- Rack-Scale In-Memory Join Processing using RDMA (CB, SL, GA, DK), pp. 1463–1475.
- SIGMOD-2015-HuLWTGY #automation #documentation #named #social #social media
- DocRicher: An Automatic Annotation System for Text Documents Using Social Media (QH, QL, XW, AKHT, SG, JY), pp. 901–906.
- SIGMOD-2015-NothaftMDZLYKAH #data-driven #scalability
- Rethinking Data-Intensive Science Using Scalable Analytics Systems (FAN, MM, TD, ZZ, UL, CY, JK, AA, JH, ML, MJF, ADJ, DAP), pp. 631–646.
- SIGMOD-2015-TuR #named #query
- DunceCap: Query Plans Using Generalized Hypertree Decompositions (ST, CR), pp. 2077–2078.
- SIGMOD-2015-WongHFXL #approach #as a service #database #named #parallel
- Thrifty: Offering Parallel Database as a Service using the Shared-Process Approach (PW, ZH, ZF, WX, EL), pp. 1063–1068.
- SIGMOD-2015-XiaoBME #metadata #summary
- Even Metadata is Getting Big: Annotation Summarization using InsightNotes (DX, AB, TM, MYE), pp. 1409–1414.
- SIGMOD-2015-YanZHSMZM #detection #distributed
- Distributed Outlier Detection using Compressive Sensing (YY, JZ, BH, XS, JM, ZZ, TM), pp. 3–16.
- SIGMOD-2015-ZhangCPSX #graph #statistics
- Private Release of Graph Statistics using Ladder Functions (JZ, GC, CMP, DS, XX), pp. 731–745.
VLDB-2015-DeutchGM #datalog #query #source code- Selective Provenance for Datalog Programs Using Top-K Queries (DD, AG, YM), pp. 1394–1405.
- VLDB-2015-HeCMPS #named #synthesis
- DPT: Differentially Private Trajectory Synthesis Using Hierarchical Reference Systems (XH, GC, AM, CMP, DS), pp. 1154–1165.
- VLDB-2015-HeGC #corpus #named #semantics
- SEMA-JOIN: Joining Semantically-Related Tables Using Big Table Corpora (YH, KG, XC), pp. 1358–1369.
- VLDB-2015-LazersonSKSGS #distributed #monitoring
- Monitoring Distributed Streams using Convex Decompositions (AL, IS, DK, AS, MNG, VS), pp. 545–556.
- VLDB-2015-ParkMS #pipes and filters #probability #query
- Processing of Probabilistic Skyline Queries Using MapReduce (YP, JKM, KS), pp. 1406–1417.
- VLDB-2015-ShinWWSZR #incremental #knowledge base
- Incremental Knowledge Base Construction Using DeepDive (JS, SW, FW, CDS, CZ, CR), pp. 1310–1321.
- CSEET-2015-SedanoP #experience #student
- Enhancing Student Experience in Team-Based Project Courses Using Essence Reflection Meetings (TS, CP), pp. 10–12.
- EDM-2015-AlHarbiH #automation #modelling #segmentation #topic
- Using Topic Segmentation Models for the Automatic Organisation of MOOCs resources (GA, TH), pp. 524–527.
- EDM-2015-AnayaGLH #analysis #approach #collaboration #diagrams #network #social
- An Approach of Collaboration Analytics in MOOCs Using Social Network Analysis and Influence Diagram (ARA, JGB, EL, FHdO), pp. 492–495.
- EDM-2015-BorjiginMSZ #assessment #behaviour
- Skill Assessment Using Behavior Data in Virtual World (AB, CM, ZS, ZZ), pp. 570–571.
- EDM-2015-BotelhoAWH #performance #predict #student
- Predicting Student Aptitude Using Performance History (AFB, SAA, HW, NTH), pp. 622–623.
- EDM-2015-EmondB #classification #process #sequence #student
- Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification (BE, SB), pp. 412–415.
- EDM-2015-Fancsali #algebra #behaviour #learning #modelling #visual notation
- Confounding Carelessness? Exploring Causal Relationships Between Carelessness, Affect, Behavior, and Learning in Cognitive Tutor Algebra Using Graphical Causal Models (SF), pp. 508–511.
- EDM-2015-Feild #performance #student
- Improving Student Performance Using Nudge Analytics (JLF), pp. 464–467.
- EDM-2015-GandhiBD #education #topic #visual notation #word
- Topic Transition in Educational Videos Using Visually Salient Words (AG, AB, OD), pp. 289–296.
- EDM-2015-Geryk #comprehension #visual notation
- Using Visual Analytics Tool for Improving Data Comprehension (JG), pp. 327–334.
- EDM-2015-InwegenAWH
- Using Partial Credit and Response History to Model User Knowledge (EVI, SA, YW0, NTH), pp. 313–319.
- EDM-2015-LuoSMG #predict #student #word
- Predicting Student Grade based on Free-style Comments using Word2Vec and ANN by Considering Prediction Results Obtained in Consecutive Lessons (JL, SES, TM, KG), pp. 396–399.
- EDM-2015-MacHardyP #big data #education
- Evaluating Educational Videos using Bayesian Knowledge Tracing and Big Data (ZM, ZAP), pp. 424–427.
- EDM-2015-NicolajsenP #adaptation #collaboration #component
- Using Knowledge Components for Collaborative Filtering in Adaptive Tutoring Systems (PHN, BP), pp. 536–539.
- EDM-2015-Rihak #adaptation #modelling
- Use of Time Information in Models behind Adaptive Practice System for Building Fluency in Mathematics (JR), pp. 642–644.
ITiCSE-2015-Dickson #development #education #game studies- Using Unity to Teach Game Development: When You’ve Never Written a Game (PED), pp. 75–80.
- ITiCSE-2015-Harms15a #java
- Using Personal Robots and Myro/Java in the First Computer Science Course (DEH), p. 332.
- ITiCSE-2015-KirkpatrickP #assurance #operating system #process
- Using the Readiness Assurance Process and Metacognition in an Operating Systems Course (MSK, SP), pp. 183–188.
- ITiCSE-2015-Rubio #analysis #automation #categorisation #clustering #programming #student
- Automatic Categorization of Introductory Programming Students using Cluster Analysis (MAR), p. 340.
- ITiCSE-2015-TarmazdiVSFF #learning #visualisation
- Using Learning Analytics to Visualise Computer Science Teamwork (HT, RV, CS, KEF, NJGF), pp. 165–170.
- ITiCSE-2015-WangMSLCW #data access #education #named #visualisation
- RBACvisual: A Visualization Tool for Teaching Access Control using Role-based Access Control (MW, JM, CKS, TL, SC, CW), pp. 141–146.
SIGITE-2015-ZhouCKNCUG #collaboration #feedback #scalability #student- M-CAFE 1.0: Motivating and Prioritizing Ongoing Student Feedback During MOOCs and Large on-Campus Courses using Collaborative Filtering (MZ, AC, SK, BN, CC, KU, KG), pp. 153–158.
- ICPC-2015-CosmaM #component #comprehension #visual notation #web
- Understanding web applications using component based visual patterns (DCC, PFM), pp. 281–284.
- ICPC-2015-Escobar-AvilaVH #bytecode #categorisation
- Unsupervised software categorization using bytecode (JEA, MLV, SH), pp. 229–239.
- ICPC-2015-HillSP #evaluation #feature model
- Exploring the use of concern element role information in feature location evaluation (EH, DCS, LLP), pp. 140–150.
- ICPC-2015-JbaraF #empirical #eye tracking #how
- How programmers read regular code: a controlled experiment using eye tracking (AJ, DGF), pp. 244–254.
- ICPC-2015-LafetaMR #dynamic analysis #framework
- Framework instantiation using cookbooks constructed with static and dynamic analysis (RFL, MdAM, DR), pp. 125–128.
- ICPC-2015-MacLeodSB #developer #documentation #how
- Code, camera, action: how software developers document and share program knowledge using YouTube (LM, MAS, AB), pp. 104–114.
- ICPC-2015-SaiedABS #api #library #question #source code
- Could we infer unordered API usage patterns only using the library source code? (MAS, HA, OB, HAS), pp. 71–81.
- ICSME-2015-AbidDCM #automation #c++ #generative #natural language #summary
- Using stereotypes in the automatic generation of natural language summaries for C++ methods (NJA, ND, MLC, JIM), pp. 561–565.
- ICSME-2015-CorleyDK #feature model #learning
- Exploring the use of deep learning for feature location (CSC, KD, NAK), pp. 556–560.
- ICSME-2015-DongAS #fault #static analysis
- Practical and accurate pinpointing of configuration errors using static analysis (ZD, AA, KS), pp. 171–180.
- ICSME-2015-DorningerPK #industrial #static analysis #user interface
- Using static analysis for knowledge extraction from industrial User Interfaces (BD, JP, AK), pp. 497–500.
- ICSME-2015-HardtM #empirical #evaluation #maintenance
- An empirical evaluation of ant build maintenance using Formiga (RH, EVM), pp. 201–210.
- ICSME-2015-MedicherlaKN #specification #verification
- Program specialization and verification using file format specifications (RKM, RK, SN), pp. 191–200.
- ICSME-2015-ValeM #architecture #dynamic analysis #mining #named
- Keecle: Mining key architecturally relevant classes using dynamic analysis (LdNV, MdAM), pp. 566–570.
- MSR-2015-BlincoeHD #ecosystem #git #identification
- Ecosystems in GitHub and a Method for Ecosystem Identification Using Reference Coupling (KB, FH, DD), pp. 202–211.
- MSR-2015-DonadelliZR #case study #fault #replication
- Organizational Volatility and Post-release Defects: A Replication Case Study Using Data from Google Chrome (SMD, YCZ, PCR), pp. 391–395.
- MSR-2015-WangPWG #comprehension #git #what
- What Is the Gist? Understanding the Use of Public Gists on GitHub (WW, GPC, EW, DMG), pp. 314–323.
- MSR-2015-ZanjaniKB #developer
- Using Developer-Interaction Trails to Triage Change Requests (MBZ, HHK, CB), pp. 88–98.
- MSR-2015-ZouXGYYZ #analysis #developer #empirical #non-functional #requirements #stack overflow #topic
- Which Non-functional Requirements Do Developers Focus On? An Empirical Study on Stack Overflow Using Topic Analysis (JZ, LX, WG, MY, DY, XZ), pp. 446–449.
- SANER-2015-BezemerPG #comprehension #difference #graph #performance
- Understanding software performance regressions using differential flame graphs (CPB, JP, BG), pp. 535–539.
- SANER-2015-CabotICR #open source
- Exploring the use of labels to categorize issues in Open-Source Software projects (JC, JLCI, VC, BR), pp. 550–554.
- SANER-2015-HuSLL #development #evolution #modelling #topic
- Modeling the evolution of development topics using Dynamic Topic Models (JH, XS, DL, BL), pp. 3–12.
- SANER-2015-LaverdiereBM #analysis #composition #graph
- Taint analysis of manual service compositions using Cross-Application Call Graphs (MAL, BJB, EM), pp. 585–589.
- SANER-2015-NayrollesHTL #approach #debugging #model checking #named
- JCHARMING: A bug reproduction approach using crash traces and directed model checking (MN, AHL, ST, AL), pp. 101–110.
- SANER-2015-QiuSM #graph #identification #library #morphism
- Library functions identification in binary code by using graph isomorphism testings (JQ, XS, PM), pp. 261–270.
- SCAM-2015-BonifacioCRKC #c++ #exception
- The use of C++ exception handling constructs: A comprehensive study (RB, FC, GNR, UK, RC), pp. 21–30.
- SCAM-2015-ChochlovEB #data flow #feature model
- Using changeset descriptions as a data source to assist feature location (MC, ME, JB), pp. 51–60.
- SCAM-2015-LemosPSL #code search #query #question #scalability
- Can the use of types and query expansion help improve large-scale code search? (OALL, ACdP, HS, CVL), pp. 41–50.
- SCAM-2015-PanditaJSW #api #mining
- Discovering likely mappings between APIs using text mining (RP, RPJ, SDS, LAW), pp. 231–240.
- SCAM-2015-RahmanRK #crowdsourcing #recommendation #source code
- Recommending insightful comments for source code using crowdsourced knowledge (MMR, CKR, IK), pp. 81–90.
- SCAM-2015-RenatusBE #modelling #security
- Improving prioritization of software weaknesses using security models with AVUS (SR, CB, JE), pp. 259–264.
- SCAM-2015-UddinGGR #comprehension #eye tracking #on the #visualisation
- On the comprehension of code clone visualizations: A controlled study using eye tracking (MSU, VG, CG, CKR), pp. 161–170.
ICALP-v1-2015-KhotS #approximate- Approximating CSPs Using LP Relaxation (SK, RS), pp. 822–833.
- FM-2015-0001K #bound #model checking
- Property-Driven Fence Insertion Using Reorder Bounded Model Checking (SJ, DK), pp. 291–307.
- FM-2015-AlTurkiA #distributed #framework #towards #verification #𝕂
- Towards Formal Verification of Orchestration Computations Using the 𝕂 Framework (MAA, OA), pp. 40–56.
- FM-2015-ChimdyalwarDCVC #abstraction #bound #model checking #static analysis
- Eliminating Static Analysis False Positives Using Loop Abstraction and Bounded Model Checking (BC, PD, AC, SV, AC), pp. 573–576.
- FM-2015-MirandaMR #automation #design #generative #testing #verification
- Using Simulink Design Verifier for Automatic Generation of Requirements-Based Tests (BM, HM, RR), pp. 601–604.
- FM-2015-Nakajima #behaviour #energy #maude #realtime
- Using Real-Time Maude to Model Check Energy Consumption Behavior (SN), pp. 378–394.
RTA-2015-AvanziniST #certification #complexity #proving- Certification of Complexity Proofs using CeTA (MA, CS, RT), pp. 23–39.
- SEFM-2015-JonesY #abstraction #reasoning
- Reasoning about Separation Using Abstraction and Reification (CBJ, NY), pp. 3–19.
- SEFM-2015-RochaBC #bound #c #generative #memory management #model checking #source code #testing
- Memory Management Test-Case Generation of C Programs Using Bounded Model Checking (HR, RSB, LCC), pp. 251–267.
- SEFM-2015-SavaryFLL #modelling #robust #testing
- Model-Based Robustness Testing in Event-B Using Mutation (AS, MF, ML, JLL), pp. 132–147.
ICFP-2015-SteuwerFLD #functional #generative #performance- Generating performance portable code using rewrite rules: from high-level functional expressions to high-performance OpenCL code (MS, CF, SL, CD), pp. 205–217.
- AIIDE-2015-StanescuBB #predict
- Using Lanchester Attrition Laws for Combat Prediction in StarCraft (MAS, NAB, MB), pp. 86–92.
- CHI-PLAY-2015-CollinsELG #2d #artificial reality #game studies #platform
- Alaska Steve: Using Virtual Reality to Enhance a 2D Platforming Game (LC, SE, JL, TCNG), pp. 767–770.
- CHI-PLAY-2015-HarpsteadA #analysis #design #education #empirical #game studies #learning
- Using Empirical Learning Curve Analysis to Inform Design in an Educational Game (EH, VA), pp. 197–207.
- CHI-PLAY-2015-HicksG #game studies
- Exploring Casual Exergames with Kids Using Wheelchairs (KH, KG), pp. 541–546.
- CHI-PLAY-2015-KeumRMCLBC #composition #development #game studies
- Exergame Development Using Body Composition Data for Obesity Care (JK, JHR, YJM, HC, NL, BCB, JDC), pp. 577–582.
- CHI-PLAY-2015-Schwind0HK #generative
- Determining the Characteristics of Preferred Virtual Faces Using an Avatar Generator (VS, KW0, NH, OK), pp. 221–230.
- CIG-2015-Garcia-SanchezT #automation #generative #programming #search-based #towards
- Towards automatic StarCraft strategy generation using genetic programming (PGS, APT, AMM, GS, JJMG), pp. 284–291.
- CIG-2015-OliveiraM #game studies #performance #realtime
- Creating efficient walls using potential fields in real-time strategy games (CFdO, CAGM), pp. 138–145.
- CIG-2015-RunarssonL #approximate #evaluation #game studies #on the
- On imitating Connect-4 game trajectories using an approximate n-tuple evaluation function (TPR, SML), pp. 208–213.
- CIG-2015-SatoIW #estimation #monte carlo #multi
- Estimation of player's preference for cooperative RPGs using multi-strategy Monte-Carlo method (NS, KI, TW), pp. 51–59.
- DiGRA-2015-BartonSQMKK #bias #design #game studies #reduction
- The Use of Theory in Designing a Serious Game for the Reduction of Cognitive Biases (MB, CS, MMQ, CKM, KSK, JK).
- DiGRA-2015-MarczakSH #comprehension #experience #matrix #similarity
- Understanding Player Experience Through the Use of Similarity Matrix (RM, GS, PH).
- DiGRA-2015-Warpefelt #visual notation
- Cues and insinuations: Indicating affordances of non-player character using visual indicators (HW).
- FDG-2015-IsaksenGN #analysis #game studies
- Exploring Game Space Using Survival Analysis (AI, DG, AN).
- FDG-2015-KaoH15b #game studies #learning
- Exploring the Construction, Play, Use of Virtual Identities in a STEM Learning Game (DK, DFH).
- FDG-2015-Martens #game studies #proving
- Using Proof Theory to Study Game Mechanics (CM).
- FDG-2015-ReuterGS #automation #detection #game studies #multi #petri net
- Detecting structural deadlocks in Multiplayer Games using automatically generated Petri Nets (CR0, SG0, RS).
- FDG-2015-RyanKMW15a #analysis #game studies #semantics #tool support
- Tools for Game Discovery Built Using Latent Semantic Analysis (JOR, EK, MM, NWF).
- VS-Games-2015-BrichRFWBMDRS0 #game studies #named #research
- LiverDefense: Using a Tower Defense Game as a Customisable Research Tool (JB, KR, JF, MW, AB, SM, TD, VR, CS, MW0), pp. 1–8.
- VS-Games-2015-Cejka #detection
- Continuous Collision Detection Using Tetrahedral Structures (JC), pp. 1–4.
- VS-Games-2015-DiazDHS #development #game studies #learning #multi #online #video
- Explicit Fun, Implicit Learning in Multiplayer Online Battle Arenas: Methodological Proposal for Studying the Development of Cognitive Skills Using Commercial Video Games (CMCD, BD, HH, JWS), pp. 1–3.
- VS-Games-2015-DiazWLT #game studies #visitor
- Your Answer Will Make an Impression. Using Quiz Game Mechanics for the Collection of Visitor Data at an Exhibition (MGAD, UW, ML, MT), pp. 1–4.
- VS-Games-2015-RobbWW #design #development #game studies
- The Development of TASTER, a Cognitive Training Game Using Human-Centered Design, Tailored for Children with Global and Specific Cognitive Impairments (NR, AW, KW), pp. 1–2.
- VS-Games-2015-WilhelmssonEBO #design #game studies #visual notation
- Accessible Game Culture Using Inclusive Game Design - Participating in a Visual Culture That You Cannot See (UW, HE, JB, PAÖ), pp. 1–8.
GCM-2015-BottoniNP #constraints #contract #modelling #policy- Conditions, Constraints and Contracts: On the Use of Annotations for Policy Modeling (PB, RN, FPP), pp. 18–33.
ICGT-2015-Bruggink0NZ #graph #graph transformation #proving #termination- Proving Termination of Graph Transformation Systems Using Weighted Type Graphs over Semirings (HJSB, BK, DN, HZ), pp. 52–68.
- ICGT-2015-Stuckrath #analysis #graph transformation #named #verification
- Uncover: Using Coverability Analysis for Verifying Graph Transformation Systems (JS), pp. 266–274.
- ICGT-2015-WeberDP #formal method #graph transformation #monitoring
- Using Graph Transformations for Formalizing Prescriptions and Monitoring Adherence (JHW, SD, MP), pp. 205–220.
CHI-2015-AsenieroWLRTC #named #release planning #visualisation- STRATOS: Using Visualization to Support Decisions in Strategic Software Release Planning (BAA, TW, DL, GR, AT, SC), pp. 1479–1488.
- CHI-2015-BachynskyiPOSW #case study #comparative #performance #simulation
- Performance and Ergonomics of Touch Surfaces: A Comparative Study using Biomechanical Simulation (MB, GP, AO, JS, TW), pp. 1817–1826.
- CHI-2015-BellottiATGDC #modelling #motivation #peer-to-peer
- A Muddle of Models of Motivation for Using Peer-to-Peer Economy Systems (VB, AA, DT, CG, KD, JMC), pp. 1085–1094.
- CHI-2015-BentleyC #composition #mobile
- The Composition and Use of Modern Mobile Phonebooks (FRB, YYC), pp. 2749–2758.
- CHI-2015-DaltonCM
- Display Blindness?: Looking Again at the Visibility of Situated Displays using Eye-tracking (NSD, EC, PM), pp. 3889–3898.
- CHI-2015-DamianTBSLA #behaviour #feedback #interactive #realtime #social
- Augmenting Social Interactions: Realtime Behavioural Feedback using Social Signal Processing Techniques (ID, CSST, TB, JS, KL, EA), pp. 565–574.
- CHI-2015-FleckCR #bound #multi
- Balancing Boundaries: Using Multiple Devices to Manage Work-Life Balance (RF, ALC, RAVR), pp. 3985–3988.
- CHI-2015-GerlingML #game studies #video
- Long-Term Use of Motion-Based Video Games in Care Home Settings (KMG, RLM, CL), pp. 1573–1582.
- CHI-2015-GoelZVP #detection #flexibility #gesture #named
- Tongue-in-Cheek: Using Wireless Signals to Enable Non-Intrusive and Flexible Facial Gestures Detection (MG, CZ, RV, SNP), pp. 255–258.
- CHI-2015-GrevetG #prototype #scalability #social
- Piggyback Prototyping: Using Existing, Large-Scale Social Computing Systems to Prototype New Ones (CG, EG), pp. 4047–4056.
- CHI-2015-GunaratneN #behaviour #performance #user interface
- Informing and Improving Retirement Saving Performance using Behavioral Economics Theory-driven User Interfaces (JG, ON), pp. 917–920.
- CHI-2015-HaqueNV #named
- Myopoint: Pointing and Clicking Using Forearm Mounted Electromyography and Inertial Motion Sensors (FH, MN, DV), pp. 3653–3656.
- CHI-2015-HiguchiCCZL #experience #named
- ImmerseBoard: Immersive Telepresence Experience using a Digital Whiteboard (KH, YC, PAC, ZZ, ZL), pp. 2383–2392.
- CHI-2015-HolzBK #identification #mobile #named
- Bodyprint: Biometric User Identification on Mobile Devices Using the Capacitive Touchscreen to Scan Body Parts (CH, SB, MK), pp. 3011–3014.
- CHI-2015-HourcadeMWP #analysis #exclamation
- Look, My Baby Is Using an iPad! An Analysis of YouTube Videos of Infants and Toddlers Using Tablets (JPH, SLM, DW, LP), pp. 1915–1924.
- CHI-2015-HydeCKH #interactive #persuasion
- Using an Interactive Avatar’s Facial Expressiveness to Increase Persuasiveness and Socialness (JH, EJC, SBK, JKH), pp. 1719–1728.
- CHI-2015-JonesCDTPDH #delphi #information management
- “For Telling” the Present: Using the Delphi Method to Understand Personal Information Management Practices (WJ, RC, AD, JT, MAPQ, JDD, BMH), pp. 3513–3522.
- CHI-2015-KatanGF #development #interactive #interface #machine learning #people
- Using Interactive Machine Learning to Support Interface Development Through Workshops with Disabled People (SK, MG, RF), pp. 251–254.
- CHI-2015-KosmallaDK #automation #metric #named #recognition
- ClimbSense: Automatic Climbing Route Recognition using Wrist-worn Inertia Measurement Units (FK, FD, AK), pp. 2033–2042.
- CHI-2015-LeeLCWSK #education #interactive #online #social
- Using Time-Anchored Peer Comments to Enhance Social Interaction in Online Educational Videos (YCL, WCL, FYC, HCW, CYS, JTK), pp. 689–698.
- CHI-2015-LugerURG #design #game studies #process
- Playing the Legal Card: Using Ideation Cards to Raise Data Protection Issues within the Design Process (EL, LU, TR, MG), pp. 457–466.
- CHI-2015-MaiorPSW #human-computer #reliability
- Examining the Reliability of Using fNIRS in Realistic HCI Settings for Spatial and Verbal Tasks (HAM, MP, SCS, MLW), pp. 3039–3042.
- CHI-2015-MariakakisGAPW #mobile #named
- SwitchBack: Using Focus and Saccade Tracking to Guide Users’ Attention for Mobile Task Resumption (AM, MG, MTIA, SNP, JOW), pp. 2953–2962.
- CHI-2015-ParkPN
- The Trial of Bendi in a Coffeehouse: Use of a Shape-Changing Device for a Tactile-Visual Phone Conversation (YP, JP, TJN), pp. 2181–2190.
- CHI-2015-PatelO
- Contextual Influences on the Use and Non-Use of Digital Technology While Exercising at the Gym (MP, AAO), pp. 2923–2932.
- CHI-2015-PfeifferDSAR
- Cruise Control for Pedestrians: Controlling Walking Direction using Electrical Muscle Stimulation (MP, TD, SS, FA, MR), pp. 2505–2514.
- CHI-2015-PreistJ #education #game studies #motivation
- The Use of Games as Extrinisic Motivation in Education (CP, RJ), pp. 3735–3738.
- CHI-2015-SimeoneVG #artificial reality #case study #design #experience #physics
- Substitutional Reality: Using the Physical Environment to Design Virtual Reality Experiences (ALS, EV, HG), pp. 3307–3316.
- CHI-2015-SlegersRVD #elicitation #game studies #research #user interface
- Using Game Principles in UX Research: A Board Game for Eliciting Future User Needs (KS, SR, JV, PD), pp. 1225–1228.
- CHI-2015-TholanderN #experience #performance
- Snot, Sweat, Pain, Mud, and Snow: Performance and Experience in the Use of Sports Watches (JT, SN), pp. 2913–2922.
- CHI-2015-VertanenMERK #mobile #named #performance
- VelociTap: Investigating Fast Mobile Text Entry using Sentence-Based Decoding of Touchscreen Keyboard Input (KV, HM, JE, SR, POK), pp. 659–668.
- CHI-2015-WangGXZYB #interactive #named #privacy #visualisation
- VeilMe: An Interactive Visualization Tool for Privacy Configuration of Using Personality Traits (YW, LG, AX, MXZ, HY, HB), pp. 817–826.
- CHI-2015-ZugerF #developer #predict
- Interruptibility of Software Developers and its Prediction Using Psycho-Physiological Sensors (MZ, TF), pp. 2981–2990.
CSCW-2015-ChangHT #recommendation- Using Groups of Items to Bootstrap New Users in Recommender Systems (SC, FMH, LGT), pp. 1258–1269.
- CSCW-2015-FreitasD15a #detection #multi
- Using Multiple Contexts to Detect and Form Opportunistic Groups (AAdF, AKD), pp. 1612–1621.
- CSCW-2015-KaziunasBJCHA #health
- Transition and Reflection in the Use of Health Information: The Case of Pediatric Bone Marrow Transplant Caregivers (EK, AGB, JJ, SWC, DAH, MSA), pp. 1763–1774.
- CSCW-2015-MaddockSASOM #behaviour #multi #online
- Characterizing Online Rumoring Behavior Using Multi-Dimensional Signatures (JM, KS, HJAH, DES, MO, RMM), pp. 228–241.
- CSCW-2015-ProstMT #design #energy #towards
- From Awareness to Empowerment: Using Design Fiction to Explore Paths towards a Sustainable Energy Future (SP, EEM, MT), pp. 1649–1658.
- CSCW-2015-XuRDB #design #feedback #process
- A Classroom Study of Using Crowd Feedback in the Iterative Design Process (AX, HR, SPD, BPB), pp. 1637–1648.
DHM-EH-2015-BoZDYWF #hybrid #kernel #performance #recognition- Hybrid BFO-PSO and Kernel FCM for the Recognition of Pilot Performance Influenced by Simulator Movement Using Diffusion Maps (JB, YBZ, LD, BTY, QW, SF), pp. 239–247.
- DHM-EH-2015-GieserBM #artificial reality #gesture #realtime #recognition
- Real-Time Static Gesture Recognition for Upper Extremity Rehabilitation Using the Leap Motion (SNG, AB, FM), pp. 144–154.
- DHM-EH-2015-KollingKHC #design #evaluation #feedback #interactive #process
- Estimating Ergonomic Comfort During the Process of Mechanism Design by Interaction with a Haptic Feedback-System — Evaluation of Simulated and Kinesthetically Displayed Mechanisms Using the Haptic Feedback System RePlaLink (TK, MK, MH, BC), pp. 62–73.
- DHM-EH-2015-MeryS #modelling #requirements
- Analyzing Requirements Using Environment Modelling (DM, NKS), pp. 345–357.
- DHM-EH-2015-NakamuraKKMK #development #self #student
- Development of a Self-learning System for Chest Auscultation Skills Using an RFID Reader for Nursing Students (MN, KK, YK, JM, MKP), pp. 474–481.
- DHM-EH-2015-UchidaHKEMOUG #analysis #process
- Process Analysis of the Hand Lay-Up Method Using CFRP Prepreg Sheets (TU, HH, KK, AE, MM, JO, TU, AG), pp. 227–236.
- DHM-EH-2015-ZhengBISEL #behaviour #monitoring
- Driving-Behavior Monitoring Using an Unmanned Aircraft System (UAS) (CZ, AB, WI, IS, EE, KL), pp. 305–312.
- DHM-HM-2015-FurukawaTKG #evaluation #image
- Evaluation of Kimono Clothes in Kyo-Yuzen-Zome using Image (TF, YT, NK, AG), pp. 277–288.
- DUXU-DD-2015-AsthanaS #modelling #named #testing #usability #xml
- Maareech: Usability Testing Tool for Voice Response System Using XML Based User Models (SA, PS), pp. 101–112.
- DUXU-IXD-2015-AkerO #effectiveness #interactive #social #social media
- Social Media Interactions and the Use of Third-Party Management Applications on Effectiveness and Perception of Information (ÇA, ÖÖ), pp. 3–12.
- DUXU-IXD-2015-DasBRD #co-evolution #design #generative
- The Use of Generative Techniques in Co-design of mHealth Technology and Healthcare Services for COPD Patients (AD, SB, JR, YD), pp. 587–595.
- DUXU-IXD-2015-HalbeyKZ
- Going on a Road-Trip with My Electric Car: Acceptance Criteria for Long-Distance-Use of Electric Vehicles (JH, SK, MZ), pp. 473–484.
- DUXU-IXD-2015-IwamotoKM #analysis #case study
- A Study of Conversation Support System Between the Elderly Person and Young Adults by Using Facial Expression Analysis (MI, NK, KM), pp. 616–627.
- DUXU-UI-2015-AyanogluBTD #artificial reality #case study
- Effects of Packages’ Color as a Cue for Hazard-Related Perceptions: A Study Using Virtual Reality (HA, RB, JT, ED), pp. 3–13.
- DUXU-UI-2015-DuWDXJ #case study #metric
- Study on Operating Clearance Measurement of Some Connectors by Using Motion Capture (HD, LW, LD, YX, CJ), pp. 45–53.
- DUXU-UI-2015-LiHF #quality #requirements #scalability #user interface
- Scaling Preferences of Different Stakeholders — Using the Example of Prioritizing Quality Requirements on User Interface Texts (YL, TH, PF), pp. 75–86.
- HCI-DE-2015-Hensely-Schinkinger #design
- The Definition and Use of Personas in the Design of Technologies for Informal Caregivers (SHS, AFPdC, MG, HT), pp. 202–213.
- HCI-DE-2015-SantosFD #case study #evaluation #heuristic #set #visualisation
- Heuristic Evaluation in Information Visualization Using Three Sets of Heuristics: An Exploratory Study (BSS, BQF, PD), pp. 259–270.
- HCI-DE-2015-SantosST #interactive #open source #visualisation
- Interactive Clinical Pedigree Visualization Using an Open Source Pedigree Drawing Engine (JMS, BSS, LT), pp. 405–414.
- HCI-DE-2015-SchutzSO
- Using Diary Studies to Evaluate Railway Dispatching Software (IS, AS, AO), pp. 248–258.
- HCI-DE-2015-SugiuraSO #implementation #metric #security
- Improving IT Security Through Security Measures: Using Our Game-Theory-Based Model of IT Security Implementation (MS, HS, TO), pp. 82–95.
- HCI-DE-2015-WatsonS #assessment
- Using Readers’ and Organizations’ Goals to Guide Assessment of Success in Information Websites (RBW, JHS), pp. 283–294.
- HCI-IT-2015-BandeiraCXK #gesture #interface
- Using Gesture-Based Interfaces to Control Robots (GMB, MC, BHX, JK), pp. 3–12.
- HCI-IT-2015-FukumotoTE #detection
- Improvement of Accuracy in Remote Gaze Detection for User Wearing Eyeglasses Using Relative Position Between Centers of Pupil and Corneal Sphere (KF, TT, YE), pp. 13–23.
- HCI-IT-2015-GuXCZ
- To Write not Select, a New Text Entry Method Using Joystick (ZG, XX, CC, YZ), pp. 35–43.
- HCI-IT-2015-HakodaKSST #bound #gesture #mobile #named
- AirFlip: A Double Crossing In-Air Gesture Using Boundary Surfaces of Hover Zone for Mobile Devices (HH, TK, KS, BS, JT), pp. 44–53.
- HCI-IT-2015-KondoTT #communication #smarttech
- Information Select and Transfer Between Touch Panel and Wearable Devices Using Human Body Communication (YK, ST, JT), pp. 208–216.
- HCI-IT-2015-KuribaraST
- Mouse Augmentation Using a Malleable Mouse Pad (TK, BS, JT), pp. 217–226.
- HCI-IT-2015-MullerLBSKSW #data-driven #network #overview #predict
- Using Neural Networks for Data-Driven Backchannel Prediction: A Survey on Input Features and Training Techniques (MM, DL, LB, MS, KK, SS, AW), pp. 329–340.
- HCI-IT-2015-MurataM #analysis #eye tracking
- Nonlinear Dynamical Analysis of Eye Movement Characteristics Using Attractor Plot and First Lyapunov Exponent (AM, TM), pp. 78–85.
- HCI-IT-2015-Nagaraju #framework #gesture
- Swift Gestures: Seamless Bend Gestures Using Graphics Framework Capabilities (SN), pp. 118–129.
- HCI-UC-2015-AzhariF #approach #experience #social #social media #user interface
- Using a Lexical Approach to Investigate User Experience of Social Media Applications (AA, XF), pp. 15–24.
- HCI-UC-2015-ClarkeBK #experience #question #what
- What Learnability Issues Do Primary Care Physicians Experience When Using CPOE? (MAC, JLB, MSK), pp. 373–383.
- HCI-UC-2015-OhJK #approach #human-computer #simulation
- Simulation of an Affordance-Based Human-Machine Cooperative Control Model Using an Agent-Based Simulation Approach (YgO, IJ, NK), pp. 226–237.
- HCI-UC-2015-Ujita #analysis #reliability
- Accident Analysis by Using Methodology of Resilience Engineering, High Reliability Organization, and Risk Literacy (HU), pp. 358–369.
- HIMI-IKC-2015-FilhoHTJM #smarttech
- Using Wearable and Contextual Computing to Optimize Field Engineering Work Practices (RSSF, CLH, AT, JJ, PM), pp. 522–533.
- HIMI-IKC-2015-HamaguchiMTKN #design #generative #matrix
- A Method for Generation and Check of Alarm Configurations Using Cause-Effect Matrices for Plant Alarm System Design (TH, BM, KT, NK, MN), pp. 549–556.
- HIMI-IKC-2015-ItaiM #development #interactive
- Study About Creation of “Maai” Involving Intention Using Rhythm Controller — Development of Maai Creating Agent and Interaction Experiments Between Human and Agent (SI, YM), pp. 599–609.
- HIMI-IKC-2015-KajitaTMI #3d #design
- Designing the Embodied Shadow Media Using Virtual Three-Dimensional Space (YK, TT, YM, SI), pp. 610–621.
- HIMI-IKC-2015-MatsudaOHT #analysis #automation #generative #multi #problem #testing
- Analysis of Multiple-Choice Tests Through Erroneous Choices Using a Technique of Automatic Problem Generation (NM, HO, TH, HT), pp. 362–369.
- HIMI-IKC-2015-MayerBPGV #automation #generative #process #visualisation
- Automatic Generation of Integrated Process Data Visualizations Using Human Knowledge (FM, UB, DP, DG, BVH), pp. 488–498.
- HIMI-IKC-2015-OliveiraCBA #artificial reality #gamification #interface #motivation
- A Head-up Display with Augmented Reality and Gamification for an E-Maintenance System: Using Interfaces and Gamification to Motivate Workers in Procedural Tasks (AO, NC, LCB, RBdA), pp. 499–510.
- HIMI-IKC-2015-SturreCVS #assessment #eye tracking
- Using Eye Movements to Test Assumptions of the Situation Present Assessment Method (LS, DC, KPLV, TZS), pp. 45–52.
- HIMI-IKC-2015-TogawaK #collaboration #framework
- Disaster Recovery Framework for e-Learning Environment Using Private Cloud Collaboration and Emergency Alerts (ST, KK), pp. 588–596.
- HIMI-IKC-2015-UeokaK #interactive
- Fortune Air: An Interactive Fortune Telling System Using Vortex Air Cannon (RU, NK), pp. 646–656.
- HIMI-IKC-2015-UjitokoH #interface
- Application of the Locomotion Interface Using Anthropomorphic Finger Motion (YU, KH), pp. 666–674.
- HIMI-IKD-2015-AraiOM #web
- A Filtering System of Web History Using the Browsing Characteristic (KA, MO, HM), pp. 273–279.
- HIMI-IKD-2015-ChouSW #case study #quality
- Improving Service Quality by Prioritizing Service Attributes Using SERVQUAL and Kano Model — A Case Study of Nursing Home in Taiwan (CMC, CS, SKW), pp. 513–525.
- HIMI-IKD-2015-ItouNM #information management #twitter
- Travel-Information Sharing System Using Tweets with Location Information (JI, KN, JM), pp. 526–534.
- HIMI-IKD-2015-IwamotoH #induction
- Induction of a Relaxed State Using a Vibration Stimulus Based on the Respiratory Cycle (NI, HH), pp. 386–395.
- HIMI-IKD-2015-KalkattawiN #ubiquitous
- Ubiquitous Healthcare Systems: Improving the Adherence Level within Diabetic Medication Using Cloud-Based Reminder System (MK, TN), pp. 535–546.
- HIMI-IKD-2015-KastratiIY #classification #documentation #framework
- A General Framework for Text Document Classification Using SEMCON and ACVSR (ZK, ASI, SYY), pp. 310–319.
- HIMI-IKD-2015-KotaniIAS #interface #variability
- Changes in Heart Rate Variability by Using Tactile Thermal Interface Device (KK, SI, TA, SS), pp. 405–411.
- HIMI-IKD-2015-MatsunoAIMM
- Computer Input System Using Eye Glances (SM, KA, NI, TM, KM), pp. 425–432.
- HIMI-IKD-2015-MorizumiA #analysis
- Analysis Using Purchasing Data in Japan (RM, YA), pp. 640–647.
- HIMI-IKD-2015-SasajimaOOS #communication #twitter #visualisation
- Proposal of a Visualization Method to Support Informal Communication Using Twitter Attributes (RS, KO, MO, AS), pp. 107–114.
- HIMI-IKD-2015-SuzukiNSTH #artificial reality #behaviour
- Changing Drinking Behavior and Beverage Consumption Using Augmented Reality (ES, TN, SS, TT, MH), pp. 648–660.
- HIMI-IKD-2015-YoshinoO
- Proposal of a Data Presentation Technique Using Four-Frame Cartoon Expression for a LifeLog System (TY, IO), pp. 235–246.
- LCT-2015-BoonbrahmKB #artificial reality #learning #student
- Using Augmented Reality Technology in Assisting English Learning for Primary School Students (SB, CK, PB), pp. 24–32.
- LCT-2015-DalipiYK #analysis #performance #semantics
- Enhancing the Learner’s Performance Analysis Using SMEUS Semantic E-learning System and Business Intelligence Technologies (FD, SYY, ZK), pp. 208–217.
- LCT-2015-HiramatsuIISS #case study #communication #mobile
- A Study to Activate Communication by Using SNS on Mobile Phone — An Essay Lesson at the Elementary School (YH, AI, KI, FS, FS), pp. 492–502.
- LCT-2015-IbanezN #design #implementation #multi
- Contextualization of Archaeological Findings Using Virtual Worlds. Issues on Design and Implementation of a Multiuser Enabled Virtual Museum (LAHI, VBN), pp. 384–393.
- LCT-2015-PyperLWJ #mobile #personalisation
- The Potential Use of the Flexilevel Test in Providing Personalised Mobile E-Assessments (AP, ML, PW, AJ), pp. 271–278.
- LCT-2015-SalazarOD #adaptation #education #mobile #multi #personalisation #ubiquitous
- Adaptive and Personalized Educational Ubiquitous Multi-Agent System Using Context-Awareness Services and Mobile Devices (OMS, DAO, NDD), pp. 301–312.
- LCT-2015-SebilloTVPG #artificial reality #interface
- The Use of Augmented Reality Interfaces for On-site Crisis Preparedness (MS, GT, GV, LP, AG), pp. 136–147.
- LCT-2015-Sein-EchaluceBG #education #information management #social
- A Knowledge Management System to Classify Social Educational Resources Within a Subject Using Teamwork Techniques (MLSE, ÁFB, FJGP, MÁCG), pp. 510–519.
- SCSM-2015-KastratiIYD #analysis #network #online #social
- Analysis of Online Social Networks Posts to Investigate Suspects Using SEMCON (ZK, ASI, SYY, FD), pp. 148–157.
- SCSM-2015-ManssourSSFS #image #network #social #visualisation
- Using Information Visualization Techniques to Improve the Perception of the Organizations’ Image on Social Networks (IHM, MSS, CQS, AJF, FTS), pp. 55–66.
CAiSE-2015-Francescomarino #workflow- Completing Workflow Traces Using Action Languages (CDF, CG, ST, IVS), pp. 314–330.
- CAiSE-2015-TsuchiyaWFOM #configuration management #feedback #interactive #requirements #traceability
- Interactive Recovery of Requirements Traceability Links Using User Feedback and Configuration Management Logs (RT, HW, YF, KO, RM), pp. 247–262.
ICEIS-v1-2015-BorgesDRAS #approach #generative- An Economic Approach for Generation of Train Driving Plans using Continuous Case-based Planning (APB, OBD, RR, BCÁ, EES), pp. 440–451.
- ICEIS-v1-2015-BouakkazLO #distance #named #similarity
- GOTA — Using the Google Similarity Distance for OLAP Textual Aggregation (MB, SL, YO), pp. 121–127.
- ICEIS-v1-2015-Castanon-PugaSG #algorithm #data mining #fuzzy #logic #mining #mobile
- Hybrid-Intelligent Mobile Indoor Location Using Wi-Fi Signals — Location Method Using Data Mining Algorithms and Type-2 Fuzzy Logic Systems (MCP, ASC, CGP, GLS, MFP, EAT), pp. 609–615.
- ICEIS-v1-2015-Marques-LucenaA #framework #information management
- Knowledge Management Framework using Wiki-based Front-end Modules (CML, CA, SK, JS), pp. 79–86.
- ICEIS-v1-2015-MpindaMSR #database #graph #simulation
- Graph Database Application using Neo4j — Railroad Planner Simulation (SATM, LGM, MTPS, MXR), pp. 399–403.
- ICEIS-v1-2015-RezendeJ #concurrent #process #workflow
- Deadlock Avoidance in Interorganizational Business Processes using a Possibilistic WorkFlow Net (LPdR, SJ), pp. 429–439.
- ICEIS-v1-2015-Roos-FrantzBFSF #concept #integration #modelling #petri net #simulation
- Using Petri Nets to Enable the Simulation of Application Integration Solutions Conceptual Models (FRF, MB, RZF, SS, VBF), pp. 87–96.
- ICEIS-v1-2015-SarmentoCG #network #streaming
- Streaming Networks Sampling using top-K Networks (RS, MC, JG), pp. 228–234.
- ICEIS-v1-2015-VaroneA #multi
- Multi-modal Transportation with Public Transport and Ride-sharing — Multi-modal Transportation using a Path-based Method (SV, KA), pp. 479–486.
- ICEIS-v2-2015-AizebojeP #approach #pointer
- An Approach to using a Laser Pointer as a Mouse (JA, TP), pp. 543–552.
- ICEIS-v2-2015-AlahmadiLN #detection #internet #process #profiling
- Using Internet Activity Profiling for Insider-threat Detection (BAA, PAL, JRCN), pp. 709–720.
- ICEIS-v2-2015-Brant-RibeiroAM #approach #interactive #modelling #petri net #web
- A User-centered Approach for Modeling Web Interactions Using Colored Petri Nets (TBR, RDA, IM, MSS, RGC), pp. 37–48.
- ICEIS-v2-2015-FrantzSRYE #ecosystem #integration #markov #on the #process
- On using Markov Decision Processes to Model Integration Solutions for Disparate Resources in Software Ecosystems (RZF, SS, FRF, IY, MTME), pp. 260–267.
- ICEIS-v2-2015-JaouachiKHHJ #image #ontology #rdf #semantics #web
- Semantic Annotation of Images Extracted from the Web using RDF Patterns and a Domain Ontology (RTJ, MTK, NH, OH, MBJ), pp. 137–144.
- ICEIS-v2-2015-KamalKVB #delivery #performance
- Efficient Use of Voice as a Channel for Delivering Public Services (KKK, MK, BV, KB), pp. 626–631.
- ICEIS-v2-2015-MagnavitaNM #evolution
- Using EVOWAVE to Analyze Software Evolution (RCM, RLN, MGM), pp. 126–136.
- ICEIS-v2-2015-Martin-Fernandez #alias #encryption #performance
- Efficient Management of Revoked Pseudonyms in VANETs using ID-Based Cryptography (FMF, PCG, CCG), pp. 701–708.
- ICEIS-v2-2015-MendesAASNM #evolution #monitoring #named #open source #technical debt #visualisation
- VisMinerTD — An Open Source Tool to Support the Monitoring of the Technical Debt Evolution using Software Visualization (TSM, DAA, NSRA, ROS, RLN, MGM), pp. 457–462.
- ICEIS-v2-2015-PereiraD #formal method #logic #semantics #uml
- Systematic Mapping — Formalization of UML Semantics using Temporal Logic (VP, MED), pp. 486–493.
- ICEIS-v2-2015-SariK #analysis #debugging #monitoring #predict
- Bug Prediction for an ATM Monitoring Software — Use of Logistic Regression Analysis for Bug Prediction (ÖS, OK), pp. 382–387.
- ICEIS-v2-2015-ThommazoCHGPBF #complexity #dependence #requirements #testing
- Using the Dependence Level Among Requirements to Priorize the Regression Testing Set and Characterize the Complexity of Requirements Change (ADT, KC, EMH, GG, JP, AB, SF), pp. 231–241.
- ICEIS-v2-2015-TrujilloOP #authoring #framework #re-engineering #validation
- Using Technical-Action-Research to Validate a Framework for Authoring Software Engineering Methods (MMT, HO, MP), pp. 15–27.
- ICEIS-v3-2015-NyameB #information management
- The Adoption and Use of Human Resource Information System (HRIS) in Ghana (PKON, RB), pp. 130–138.
- ICEIS-v3-2015-RiveroC #case study #evaluation #experience #user interface
- Using a Study to Assess User eXperience Evaluation Methods from the Point of View of Users (LR, TC), pp. 88–95.
- ICEIS-v3-2015-SaidCAB #adaptation #modelling #named #process
- BPMN4V — An Extension of BPMN for Modelling Adaptive Processes using Versions (IBS, MAC, EA, RB), pp. 258–267.
- ICEIS-v3-2015-SilvaMLFNS #architecture #experience #health #information management #modelling
- An Experience of using SoaML for Modeling a Service-Oriented Architecture for Health Information Systems (FGS, JSSdM, JdSL, JMSF, RPCdN, MSS), pp. 322–327.
- CIKM-2015-BagdouriO #microblog #set
- Profession-Based Person Search in Microblogs: Using Seed Sets to Find Journalists (MB, DWO), pp. 593–602.
- CIKM-2015-BuchA #approximate #learning #string
- Approximate String Matching by End-Users using Active Learning (LB, AA0), pp. 93–102.
- CIKM-2015-JeongKL #on the fly
- A Flash-aware Buffering Scheme using On-the-fly Redo (KSJ, SWK, SL), pp. 1683–1686.
- CIKM-2015-MaGWLW #detection #information management #microblog #social
- Detect Rumors Using Time Series of Social Context Information on Microblogging Websites (JM, WG0, ZW, YL, KFW), pp. 1751–1754.
- CIKM-2015-MishraH #clustering #learning #multi
- Learning Task Grouping using Supervised Task Space Partitioning in Lifelong Multitask Learning (MM, JH), pp. 1091–1100.
- CIKM-2015-ParkHL #nearest neighbour #performance
- A Fast k-Nearest Neighbor Search Using Query-Specific Signature Selection (YP, HH, SgL), pp. 1883–1886.
- CIKM-2015-RoychoudhuryKB #documentation #ontology #process
- Analyzing Document Intensive Business Processes using Ontology (SR, VK, NB), pp. 1899–1902.
- CIKM-2015-SiersdorferKAZ #how #network #scalability #social
- Who With Whom And How?: Extracting Large Social Networks Using Search Engines (SS, PK, HA, SZ), pp. 1491–1500.
- CIKM-2015-Teevan #information retrieval
- Slow Search: Improving Information Retrieval Using Human Assistance (JT), p. 1.
- CIKM-2015-TuarobTSR #modelling #network #social
- Modeling Individual-Level Infection Dynamics Using Social Network Information (ST, CST, MS, NR), pp. 1501–1510.
- CIKM-2015-WangSL #distance #learning #summary
- Update Summarization using Semi-Supervised Learning Based on Hellinger Distance (DW0, SS, TL0), pp. 1907–1910.
- CIKM-2015-ZhangSWFW #crowdsourcing #quality
- Improving Label Quality in Crowdsourcing Using Noise Correction (JZ0, VSS, JW0, XF, XW0), pp. 1931–1934.
- ECIR-2015-BiyaniBCM #analysis #concurrent #online #retrieval #thread
- Using Subjectivity Analysis to Improve Thread Retrieval in Online Forums (PB, SB, CC, PM), pp. 495–500.
- ECIR-2015-ChongDL #modelling #predict #topic
- Prediction of Venues in Foursquare Using Flipped Topic Models (WHC, BTD, EPL), pp. 623–634.
- ECIR-2015-Dutta #approximate #mining #named #statistics #string
- MIST: Top-k Approximate Sub-string Mining Using Triplet Statistical Significance (SD), pp. 284–290.
- ECIR-2015-GogMP #identification #on the #statistics
- On Identifying Phrases Using Collection Statistics (SG, AM, MP), pp. 278–283.
- ECIR-2015-HagenPBS #classification #detection #sentiment #twitter
- Twitter Sentiment Detection via Ensemble Classification Using Averaged Confidence Scores (MH, MP, MB, BS), pp. 741–754.
- ECIR-2015-JameelLB #modelling #parametricity #topic
- Nonparametric Topic Modeling Using Chinese Restaurant Franchise with Buddy Customers (SJ, WL, LB), pp. 648–659.
- ECIR-2015-LiC #effectiveness
- Effective Healthcare Advertising Using Latent Dirichlet Allocation and Inference Engine (YCL, CCC), pp. 672–677.
- ECIR-2015-LimCLK #community #constraints #detection
- Detecting Location-Centric Communities Using Social-Spatial Links with Temporal Constraints (KHL, JC, CL, SK), pp. 489–494.
- ECIR-2015-LuoZDY #design
- Designing States, Actions, and Rewards for Using POMDP in Session Search (JL, SZ, XD, HY), pp. 526–537.
- ECIR-2015-MaddalenaMST #estimation
- Judging Relevance Using Magnitude Estimation (EM, SM, FS, AT), pp. 215–220.
- ICML-2015-AvronH #community #detection #personalisation #rank
- Community Detection Using Time-Dependent Personalized PageRank (HA, LH), pp. 1795–1803.
- ICML-2015-ChangYXY #detection #semantics
- Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM (XC, YY, EPX, YY), pp. 1348–1357.
- ICML-2015-LeC #learning #metric
- Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations (TL, MC), pp. 2002–2011.
- ICML-2015-SnoekRSKSSPPA #network #optimisation #scalability
- Scalable Bayesian Optimization Using Deep Neural Networks (JS, OR, KS, RK, NS, NS, MMAP, P, RPA), pp. 2171–2180.
- ICML-2015-Sohl-DicksteinW #learning
- Deep Unsupervised Learning using Nonequilibrium Thermodynamics (JSD, EAW, NM, SG), pp. 2256–2265.
- ICML-2015-SrivastavaMS #learning #video
- Unsupervised Learning of Video Representations using LSTMs (NS, EM, RS), pp. 843–852.
- ICML-2015-SunQW #optimisation #taxonomy
- Complete Dictionary Recovery Using Nonconvex Optimization (JS, QQ, JW), pp. 2351–2360.
- ICML-2015-UbaruMS #approximate #fault #matrix #rank
- Low Rank Approximation using Error Correcting Coding Matrices (SU, AM, YS), pp. 702–710.
- ICML-2015-ZhuE #approach #hybrid #probability #random
- A Hybrid Approach for Probabilistic Inference using Random Projections (MZ, SE), pp. 2039–2047.
- KDD-2015-AhnKLRW #distributed #matrix #probability #scalability
- Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC (SA, AK, NL, SR, MW), pp. 9–18.
- KDD-2015-GleichM #algorithm #graph #learning
- Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms (DFG, MWM), pp. 359–368.
- KDD-2015-IkonomovskaJD #predict #realtime
- Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection (EI, SJ, AD), pp. 1869–1878.
- KDD-2015-JohanssonD #geometry #graph #learning #similarity
- Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings (FDJ, DPD), pp. 467–476.
- KDD-2015-KotziasDFS
- From Group to Individual Labels Using Deep Features (DK, MD, NdF, PS), pp. 597–606.
- KDD-2015-MayaMMAY #clustering
- Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering (SM, KM, HM, RA, KY), pp. 1979–1988.
- KDD-2015-MomtazpourZRSR #cyber-physical #invariant
- Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression (MM, JZ, SR, RKS, NR), pp. 2009–2018.
- KDD-2015-Ojjeh #open source #realtime
- Powering Real-time Decision Engines in Finance and Healthcare using Open Source Software (BO), p. 1633.
- KDD-2015-PengKLC #approximate #clustering #rank
- Subspace Clustering Using Log-determinant Rank Approximation (CP, ZK, HL, QC), pp. 925–934.
- KDD-2015-SethiYRVR #classification #machine learning #scalability
- Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery (MS, YY, AR, RRV, SR), pp. 2069–2078.
- KDD-2015-ShanahanD #distributed #scalability
- Large Scale Distributed Data Science using Apache Spark (JGS, LD), pp. 2323–2324.
- KDD-2015-SomanchiALEG #predict
- Early Prediction of Cardiac Arrest (Code Blue) using Electronic Medical Records (SS, SA, AL, EE, RG), pp. 2119–2126.
- KDD-2015-WangYLXXCR #predict
- Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data (YW, NJY, DL, LX, XX, EC, YR), pp. 1275–1284.
- KDD-2015-WeiLMCRS #predict
- Predicting Serves in Tennis using Style Priors (XW, PL, SM, PC, MR, SS), pp. 2207–2215.
- KDD-2015-YuanBM #process #re-engineering
- Gas Concentration Reconstruction for Coal-Fired Boilers Using Gaussian Process (CY, MB, BM), pp. 2247–2256.
- KDD-2015-ZhengYX #composition #linear #modelling #topic
- Linear Time Samplers for Supervised Topic Models using Compositional Proposals (XZ, YY, EPX), pp. 1523–1532.
MLDM-2015-Babu #classification #identification- Offline Writer Identification in Tamil Using Bagged Classification Trees (SB), pp. 342–354.
- MLDM-2015-CostaFK #multi
- Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machines, Multilayer Perceptrons and Autoencoders (WC, LMGF, TSK), pp. 187–198.
- MLDM-2015-GovadaJMS #approach #hybrid #induction #learning
- Hybrid Approach for Inductive Semi Supervised Learning Using Label Propagation and Support Vector Machine (AG, PJ, SM, SKS), pp. 199–213.
- MLDM-2015-MojahedBWI #analysis #clustering #matrix #semistructured data #similarity
- Applying Clustering Analysis to Heterogeneous Data Using Similarity Matrix Fusion (SMF) (AM, JHBS, WW, BdlI), pp. 251–265.
- MLDM-2015-MoldovanM #data mining #learning #mining #performance
- Learning the Relationship Between Corporate Governance and Company Performance Using Data Mining (DM, SM), pp. 368–381.
- MLDM-2015-PatchalaBG #email
- Author Attribution of Email Messages Using Parse-Tree Features (JP, RB, SG), pp. 313–327.
- MLDM-2015-TreechalongRW #clustering
- Semi-Supervised Stream Clustering Using Labeled Data Points (KT, TR, KW), pp. 281–295.
RecSys-2015-AghdamHMB #adaptation #markov #modelling #recommendation- Adapting Recommendations to Contextual Changes Using Hierarchical Hidden Markov Models (MHA, NH, BM, RDB), pp. 241–244.
- RecSys-2015-BanksRS #game studies #recommendation
- The Recommendation Game: Using a Game-with-a-Purpose to Generate Recommendation Data (SB, RR, BS), pp. 305–308.
- RecSys-2015-ChaneyBE #network #personalisation #probability #recommendation #social
- A Probabilistic Model for Using Social Networks in Personalized Item Recommendation (AJBC, DMB, TER), pp. 43–50.
- RecSys-2015-MagnusonDM #process #recommendation #twitter
- Event Recommendation using Twitter Activity (AM, VD, DM), pp. 331–332.
SEKE-2015-CaoHH #design #evaluation #quality- Experimental Frame Design Using E-DEVSML for Software Quality Evaluation (BC, LH, JH), pp. 310–313.
- SEKE-2015-ChavezM #information retrieval #ontology #query
- An Information Retrieval Model using Query Expansion based on Ontologies in the Computer Science Domain (BGCC, AM), pp. 652–655.
- SEKE-2015-DingZ #modelling #petri net
- Modeling and Analyzing Publish Subscribe Architcture using Petri Nets (JD, DZ), pp. 589–594.
- SEKE-2015-GoswamiWS #learning #performance
- Using Learning Styles of Software Professionals to Improve their Inspection Team Performance (AG, GSW, AS), pp. 680–685.
- SEKE-2015-ManiPW #co-evolution #modelling #performance
- Exploring SOA Pattern Performance using Coupled Transformations and Performance Models (NM, DCP, CMW), pp. 552–557.
- SEKE-2015-Murillo-MoreraJ #algorithm #approach #framework #learning #predict #search-based
- A Software Defect-Proneness Prediction Framework: A new approach using genetic algorithms to generate learning schemes (JMM, MJ), pp. 445–450.
- SEKE-2015-NetoSZD #network
- Using implications from FCA to represent a two mode network data (SMN, MAJS, LEZ, SMD), pp. 256–259.
- SEKE-2015-SunSWZ #analysis #data flow #detection #fault #integer
- Improving the Accuracy of Integer Signedness Error Detection Using Data Flow Analysis (HS, CS, YW, QZ), pp. 601–606.
- SEKE-2015-TakahashiNT #automation #elicitation #feedback #requirements #topic #towards
- Towards Automatic Requirements Elicitation from Feedback Comments: Extracting Requirements Topics Using LDA (HT, HN, TT), pp. 489–494.
- SEKE-2015-Tasse #analysis #identification #metric
- Using peak analysis for identifying lagged effects between software metrics (JT), pp. 512–515.
- SEKE-2015-TrinkenreichSCS #metric #process #towards
- Toward using Business Process Intelligence to Support Incident Management Metrics Selection and Service Improvement (BT, GS, VTFC, FMS), pp. 522–527.
- SEKE-2015-TunnellA #fault #modelling #predict #release planning
- Using Time Series Models for Defect Prediction in Software Release Planning (JT, JA), pp. 451–454.
- SEKE-2015-XuB #multi #reliability
- A Reliable and Secure Cloud Storage Schema Using Multiple Service Providers (HX, DB), pp. 116–121.
SIGIR-2015-AlbakourMO #data type #identification #metadata #topic- Using Sensor Metadata Streams to Identify Topics of Local Events in the City (MDA, CM, IO), pp. 711–714.
- SIGIR-2015-AzzopardiZ #modelling #retrieval #tutorial
- Building and Using Models of Information Seeking, Search and Retrieval: Full Day Tutorial (LA, GZ), pp. 1107–1110.
- SIGIR-2015-CapraACV #complexity #difference
- Differences in the Use of Search Assistance for Tasks of Varying Complexity (RC, JA, AC, EV), pp. 23–32.
- SIGIR-2015-HaraSKF #recommendation
- Reducing Hubness: A Cause of Vulnerability in Recommender Systems (KH, IS, KK, KF), pp. 815–818.
- SIGIR-2015-Kiseleva #behaviour #information management
- Using Contextual Information to Understand Searching and Browsing Behavior (JK), p. 1059.
- SIGIR-2015-LiLZS #matrix #modelling #multi #retrieval
- Modeling Multi-query Retrieval Tasks Using Density Matrix Transformation (QL, JL, PZ, DS), pp. 871–874.
- SIGIR-2015-LiuAH #information retrieval #probability
- Using Term Location Information to Enhance Probabilistic Information Retrieval (BL, XA, JXH), pp. 883–886.
- SIGIR-2015-Lu #statistics
- Improving Search using Proximity-Based Statistics (XL), p. 1065.
- SIGIR-2015-MehrotraY #learning #query #rank
- Representative & Informative Query Selection for Learning to Rank using Submodular Functions (RM, EY), pp. 545–554.
- SIGIR-2015-Mitra #distributed #query
- Exploring Session Context using Distributed Representations of Queries and Reformulations (BM), pp. 3–12.
- SIGIR-2015-NovakBZ #image #retrieval #scalability
- Large-scale Image Retrieval using Neural Net Descriptors (DN, MB, PZ), pp. 1039–1040.
- SIGIR-2015-ParkC #concept #retrieval
- Using Key Concepts in a Translation Model for Retrieval (JHP, WBC), pp. 927–930.
- SIGIR-2015-WeiG #summary #twitter
- Gibberish, Assistant, or Master?: Using Tweets Linking to News for Extractive Single-Document Summarization (ZW, WG), pp. 1003–1006.
- SIGIR-2015-YaoSQWSH #recommendation #social
- Context-aware Point-of-Interest Recommendation Using Tensor Factorization with Social Regularization (LY, QZS, YQ, XW, AS, QH), pp. 1007–1010.
SKY-2015-Oliveira #learning- Learning the Meaning of Language and using It Creatively (HGO), p. 3.
- ECMFA-J-2012-PuissantSM15 #automation #consistency #nondeterminism
- Resolving model inconsistencies using automated regression planning (JPP, RVDS, TM), pp. 461–481.
AMT-2015-HilkenBGV #development #modelling- Iterative Development of Transformation Models by Using Classifying Terms (FH, LB, MG, AV), pp. 1–6.
- ICMT-2015-CriadoMIC #model transformation #reuse
- Enabling the Reuse of Stored Model Transformations Through Annotations (JC, SMP, LI, JC), pp. 43–58.
- ICMT-2015-MooijEHW #effectiveness #industrial #modelling
- Cost-Effective Industrial Software Rejuvenation Using Domain-Specific Models (AJM, GE, JH, HvW), pp. 66–81.
- MoDELS-2015-Fernandez-SaezC #documentation #industrial #maintenance #on the #overview #uml
- On the use of UML documentation in software maintenance: Results from a survey in industry (AMFS, DC, MG, MRVC), pp. 292–301.
- MoDELS-2015-LuddeckeSSS #modelling #network
- Modeling user intentions for in-car infotainment systems using Bayesian networks (DL, CS, JS, IS), pp. 378–385.
- MoDELS-2015-SchottleK #api #modelling #reuse
- Concern-oriented interfaces for model-based reuse of APIs (MS, JK), pp. 286–291.
- MoDELS-2015-StephanC #clone detection #detection #identification
- Identification of Simulink model antipattern instances using model clone detection (MS, JRC), pp. 276–285.
SPLC-2015-BeekFGM #analysis #product line- Using FMC for family-based analysis of software product lines (MHtB, AF, SG, FM), pp. 432–439.
- SPLC-2015-BeucheH #lifecycle #product line
- Using pure: : variants across the product line lifecycle (DB, RH), pp. 352–354.
- SPLC-2015-ChavarriagaRNCJ #case study #configuration management #experience #feature model #modelling #multi
- Using multiple feature models to specify configuration options for electrical transformers: an experience report (JC, CR, CN, RC, VJ), pp. 216–224.
- SPLC-2015-DimovskiABW #model checking #off the shelf
- Family-based model checking using off-the-shelf model checkers: extended abstract (ASD, ASAS, CB, AW), p. 397.
- SPLC-2015-DomisAB #analysis #modelling #safety #tool support #uml #variability
- Integrating variability and safety analysis models using commercial UML-based tools (DD, RA, MB), pp. 225–234.
- SPLC-2015-DudderRH #composition #design #staged #type safety
- Synthesizing type-safe compositions in feature oriented software designs using staged composition (BD, JR, GTH), pp. 398–401.
- SPLC-2015-PatelS #as a service #automation #testing #variability
- Automated testing of software-as-a-service configurations using a variability language (SP, VS), pp. 253–262.
- Onward-2015-CitoLGDKR #developer #feedback #metric #runtime
- Runtime metric meets developer: building better cloud applications using feedback (JC, PL, HCG, AD, AK, AR), pp. 14–27.
- OOPSLA-2015-VoelterDKE #c #case study #embedded
- Using C language extensions for developing embedded software: a case study (MV, AvD, BK, SE), pp. 655–674.
PLATEAU-2015-KristenssonL #lightweight #visualisation- Aiding programmers using lightweight integrated code visualization (POK, CLL), pp. 17–24.
- AdaEurope-2015-JaradatBP #analysis #maintenance #safety
- Using Sensitivity Analysis to Facilitate the Maintenance of Safety Cases (OJ, IB, SP), pp. 162–176.
- LOPSTR-2015-CaballeroMKH #automation #generative #java #testing
- Checking Java Assertions Using Automated Test-Case Generation (RC0, MM, HK, VvH), pp. 221–226.
- LOPSTR-2015-MantelMPW #analysis #automaton #composition #data flow #network
- Using Dynamic Pushdown Networks to Automate a Modular Information-Flow Analysis (HM, MMO, MP, AW), pp. 201–217.
- PADL-2015-BassedaK #logic #transaction
- State Space Planning Using Transaction Logic (RB, MK), pp. 17–33.
- PLDI-2015-BarowyGHZ #named #relational #spreadsheet
- FlashRelate: extracting relational data from semi-structured spreadsheets using examples (DWB, SG, TH, BGZ), pp. 218–228.
- PLDI-2015-CraryS #peer-to-peer
- Peer-to-peer affine commitment using bitcoin (KC, MJS), pp. 479–488.
