BibSLEIGH
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Stem learn$ (all stems)

4419 papers:

ECSAECSA-2015-KiwelekarW #architecture #learning
Learning Objectives for a Course on Software Architecture (AWK, HSW), pp. 169–180.
CASECASE-2015-ChenXZCL #effectiveness #learning #multi #optimisation #simulation
An effective learning procedure for multi-fidelity simulation optimization with ordinal transformation (RC, JX, SZ, CHC, LHL), pp. 702–707.
CASECASE-2015-FarhanPWL #algorithm #machine learning #predict #using
Predicting individual thermal comfort using machine learning algorithms (AAF, KRP, BW, PBL), pp. 708–713.
CASECASE-2015-LiX #energy #learning #multi
A multi-grid reinforcement learning method for energy conservation and comfort of HVAC in buildings (BL, LX), pp. 444–449.
CASECASE-2015-ParisACAR #behaviour #learning #markov #smarttech #using
Using Hidden Semi-Markov Model for learning behavior in smarthomes (AP, SA, NC, AEA, NR), pp. 752–757.
CASECASE-2015-SrinivasanBSSR #automation #machine learning #modelling #network #using
Modelling time-varying delays in networked automation systems with heterogeneous networks using machine learning techniques (SS, FB, GS, BS, SR), pp. 362–368.
CASECASE-2015-SundarkumarRNG #api #detection #machine learning #modelling #topic
Malware detection via API calls, topic models and machine learning (GGS, VR, IN, VG), pp. 1212–1217.
CASECASE-2015-SustoM #approach #machine learning #multi #predict
Slow release drug dissolution profile prediction in pharmaceutical manufacturing: A multivariate and machine learning approach (GAS, SFM), pp. 1218–1223.
CASECASE-2015-SuWCRT #adaptation #fuzzy #learning
Adaptive PD fuzzy control with dynamic learning rate for two-wheeled balancing six degrees of freedom robotic arm (SFS, KJW, MCC, IJR, CCT), pp. 1258–1261.
CASECASE-2015-WatteyneAV #lessons learnt #scalability
Lessons learned from large-scale dense IEEE802.15.4 connectivity traces (TW, CA, XV), pp. 145–150.
CASECASE-2015-ZhangWZZ #automaton #learning #optimisation #performance
Incorporation of ordinal optimization into learning automata for high learning efficiency (JZ, CW, DZ, MZ), pp. 1206–1211.
DACDAC-2015-SztipanovitsBNK #cyber-physical #design #lessons learnt
Design tool chain for cyber-physical systems: lessons learned (JS, TB, SN, XDK, EKJ), p. 6.
DACDAC-2015-VenkataramaniRL #classification #energy #machine learning
Scalable-effort classifiers for energy-efficient machine learning (SV, AR, JL, MS), p. 6.
DATEDATE-2015-ChenKXMLYVSCY #algorithm #array #learning
Technology-design co-optimization of resistive cross-point array for accelerating learning algorithms on chip (PYC, DK, ZX, AM, BL, JY, SBKV, JsS, YC, SY), pp. 854–859.
DATEDATE-2015-ChenM #distributed #learning #manycore #optimisation #performance
Distributed reinforcement learning for power limited many-core system performance optimization (ZC, DM), pp. 1521–1526.
DATEDATE-2015-KanounS #big data #concept #data type #detection #learning #online #scheduling #streaming
Big-data streaming applications scheduling with online learning and concept drift detection (KK, MvdS), pp. 1547–1550.
DATEDATE-2015-RenTB #detection #learning #statistics
Detection of illegitimate access to JTAG via statistical learning in chip (XR, VGT, RD(B), pp. 109–114.
DATEDATE-2015-ZhuM #linear #machine learning #optimisation #programming #using
Optimizing dynamic trace signal selection using machine learning and linear programming (CSZ, SM), pp. 1289–1292.
DocEngDocEng-2015-Paoli #documentation #what
Documents as Data, Data as Documents: What we learned about Semi-Structured Information for our Open World of Cloud & Devices (JP), p. 1.
DocEngDocEng-2015-SilvaFLCOSR #automation #documentation #machine learning #summary
Automatic Text Document Summarization Based on Machine Learning (GPeS, RF, RDL, LdSC, HO, SJS, MR), pp. 191–194.
DRRDRR-2015-FuLLQT #diagrams #learning #multi #retrieval
A diagram retrieval method with multi-label learning (SF, XL, LL, JQ, ZT).
HTHT-2015-KirchnerR #collaboration #in the cloud #learning
Collaborative Learning in the Cloud: A Cross-Cultural Perspective of Collaboration (KK, LR), pp. 333–336.
HTHT-2015-MishraDBS #analysis #incremental #learning #sentiment
Sentiment Analysis with Incremental Human-in-the-Loop Learning and Lexical Resource Customization (SM, JD, JB, ES), pp. 323–325.
SIGMODSIGMOD-2015-HuangBTRTR #machine learning #scalability
Resource Elasticity for Large-Scale Machine Learning (BH, MB, YT, BR, ST, FRR), pp. 137–152.
SIGMODSIGMOD-2015-KumarNP #learning #linear #modelling #normalisation
Learning Generalized Linear Models Over Normalized Data (AK, JFN, JMP), pp. 1969–1984.
SIGMODSIGMOD-2015-ReABCJKR #database #machine learning #question
Machine Learning and Databases: The Sound of Things to Come or a Cacophony of Hype? (CR, DA, MB, MIC, MIJ, TK, RR), pp. 283–284.
VLDBVLDB-2015-KumarJYNP #machine learning #normalisation #optimisation
Demonstration of Santoku: Optimizing Machine Learning over Normalized Data (AK, MJ, BY, JFN, JMP), pp. 1864–1875.
VLDBVLDB-2015-QianGJ #adaptation #comparison #learning
Learning User Preferences By Adaptive Pairwise Comparison (LQ, JG, HVJ), pp. 1322–1333.
ITiCSEITiCSE-2015-AlshammariAH #adaptation #education #learning #security
The Impact of Learning Style Adaptivity in Teaching Computer Security (MA, RA, RJH), pp. 135–140.
ITiCSEITiCSE-2015-AndersonNM #programming
Facilitating Programming Success in Data Science Courses through Gamified Scaffolding and Learn2Mine (PEA, TN, RAM), pp. 99–104.
ITiCSEITiCSE-2015-Annamaa #ide #learning #programming #python
Thonny, : a Python IDE for Learning Programming (AA), p. 343.
ITiCSEITiCSE-2015-Cukierman #learning #predict #process #student
Predicting Success in University First Year Computing Science Courses: The Role of Student Participation in Reflective Learning Activities and in I-clicker Activities (DC), pp. 248–253.
ITiCSEITiCSE-2015-Hamilton #education #learning
Learning and Teaching Computing Sustainability (MH), p. 338.
ITiCSEITiCSE-2015-Harms #community #learning #source code
Department Programs to Encourage and Support Service Learning and Community Engagement (DEH), p. 330.
ITiCSEITiCSE-2015-MartinezGB #comparison #concept #framework #learning #multi #programming
A Comparison of Preschool and Elementary School Children Learning Computer Science Concepts through a Multilanguage Robot Programming Platform (MCM, MJG, LB), pp. 159–164.
ITiCSEITiCSE-2015-ParreiraPC #c #named #student
PCRS-C: Helping Students Learn C (DMP, AP, MC), p. 347.
ITiCSEITiCSE-2015-QuinsonO #education #learning #programming
A Teaching System to Learn Programming: the Programmer’s Learning Machine (MQ, GO), pp. 260–265.
ITiCSEITiCSE-2015-SantosSFN #agile #development #framework #learning #mobile
Combining Challenge-Based Learning and Scrum Framework for Mobile Application Development (ARS, AS, PF, MN), pp. 189–194.
ITiCSEITiCSE-2015-SettleLS #community #learning
A Computer Science Linked-courses Learning Community (AS, JL, TS), pp. 123–128.
ITiCSEITiCSE-2015-TarmazdiVSFF #learning #using #visualisation
Using Learning Analytics to Visualise Computer Science Teamwork (HT, RV, CS, KEF, NJGF), pp. 165–170.
ITiCSEITiCSE-2015-Tudor #learning #optimisation #query #xml
Virtual Learning Laboratory about Query Optimization against XML Data (LNT), p. 348.
ICSMEICSME-2015-CorleyDK #feature model #learning
Exploring the use of deep learning for feature location (CSC, KD, NAK), pp. 556–560.
ICSMEICSME-2015-PiorkowskiFSBKH #bias #debugging #developer #how #information management
To fix or to learn? How production bias affects developers’ information foraging during debugging (DP, SDF, CS, MMB, IK, AZH, JM, CH, AH), pp. 11–20.
MSRMSR-2015-BirdCG #bibliography #code review #framework #lessons learnt
Lessons Learned from Building and Deploying a Code Review Analytics Platform (CB, TC, MG), pp. 191–201.
MSRMSR-2015-WhiteVVP #learning #repository #towards
Toward Deep Learning Software Repositories (MW, CV, MLV, DP), pp. 334–345.
STOCSTOC-2015-BarakKS #composition #learning #taxonomy
Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method (BB, JAK, DS), pp. 143–151.
STOCSTOC-2015-Bresler #graph #learning #modelling
Efficiently Learning Ising Models on Arbitrary Graphs (GB), pp. 771–782.
STOCSTOC-2015-GeHK #learning
Learning Mixtures of Gaussians in High Dimensions (RG, QH, SMK), pp. 761–770.
STOCSTOC-2015-HardtP #bound #learning
Tight Bounds for Learning a Mixture of Two Gaussians (MH, EP), pp. 753–760.
STOCSTOC-2015-LiRSS #learning #statistics
Learning Arbitrary Statistical Mixtures of Discrete Distributions (JL, YR, LJS, CS), pp. 743–752.
LATALATA-2015-Yoshinaka #boolean grammar #grammar inference #learning
Learning Conjunctive Grammars and Contextual Binary Feature Grammars (RY), pp. 623–635.
FMFM-2015-Damm #analysis #automation #lessons learnt #named #verification
AVACS: Automatic Verification and Analysis of Complex Systems Highlights and Lessons Learned (WD), pp. 18–19.
SEFMSEFM-2015-Muhlberg0DLP #learning #source code #verification
Learning Assertions to Verify Linked-List Programs (JTM, DHW, MD, GL, FP), pp. 37–52.
ICFPICFP-2015-ZhuNJ #learning #refinement
Learning refinement types (HZ, AVN, SJ), pp. 400–411.
CHICHI-2015-AmershiCDLSS #analysis #machine learning #named #performance #tool support
ModelTracker: Redesigning Performance Analysis Tools for Machine Learning (SA, MC, SMD, BL, PYS, JS), pp. 337–346.
CHICHI-2015-BerardR #assessment #human-computer #learning #similarity #towards
The Transfer of Learning as HCI Similarity: Towards an Objective Assessment of the Sensory-Motor Basis of Naturalness (FB, ARC), pp. 1315–1324.
CHICHI-2015-CaiGGM #education #named
Wait-Learning: Leveraging Wait Time for Second Language Education (CJC, PJG, JRG, RCM), pp. 3701–3710.
CHICHI-2015-DavisK #learning #student
Investigating High School Students’ Perceptions of Digital Badges in Afterschool Learning (KD, EK), pp. 4043–4046.
CHICHI-2015-KardanC #adaptation #evaluation #interactive #learning #simulation
Providing Adaptive Support in an Interactive Simulation for Learning: An Experimental Evaluation (SK, CC), pp. 3671–3680.
CHICHI-2015-KatanGF #development #interactive #interface #machine learning #people #using
Using Interactive Machine Learning to Support Interface Development Through Workshops with Disabled People (SK, MG, RF), pp. 251–254.
CHICHI-2015-Noble #learning #self
Resilience Ex Machina: Learning a Complex Medical Device for Haemodialysis Self-Treatment (PJN), pp. 4147–4150.
CHICHI-2015-NoroozMJMF #approach #learning #named #smarttech #visualisation
BodyVis: A New Approach to Body Learning Through Wearable Sensing and Visualization (LN, MLM, AJ, BM, JEF), pp. 1025–1034.
CHICHI-2015-ShovmanBSS #3d #interface #learning
Twist and Learn: Interface Learning in 3DOF Exploration of 3D Scatterplots (MMS, JLB, AS, KCSB), pp. 313–316.
CHICHI-2015-StrohmayerCB #learning #people
Exploring Learning Ecologies among People Experiencing Homelessness (AS, RC, MB), pp. 2275–2284.
CHICHI-2015-Walther-FranksS #design #game studies #learning
Robots, Pancakes, and Computer Games: Designing Serious Games for Robot Imitation Learning (BWF, JS, PS, AH, MB, RM), pp. 3623–3632.
CHICHI-2015-YannierKH #effectiveness #game studies #learning #physics #question #tablet
Learning from Mixed-Reality Games: Is Shaking a Tablet as Effective as Physical Observation? (NY, KRK, SEH), pp. 1045–1054.
CSCWCSCW-2015-Anya #design #exclamation #question #what
Bridge the Gap!: What Can Work Design in Crowdwork Learn from Work Design Theories? (OA), pp. 612–627.
CSCWCSCW-2015-ChengB #classification #hybrid #machine learning #named
Flock: Hybrid Crowd-Machine Learning Classifiers (JC, MSB), pp. 600–611.
CSCWCSCW-2015-CoetzeeLFHH #interactive #learning #scalability
Structuring Interactions for Large-Scale Synchronous Peer Learning (DC, SL, AF, BH, MAH), pp. 1139–1152.
CSCWCSCW-2015-DornSS #collaboration #learning
Piloting TrACE: Exploring Spatiotemporal Anchored Collaboration in Asynchronous Learning (BD, LBS, AS), pp. 393–403.
CSCWCSCW-2015-JiaWXRC #behaviour #learning #online #privacy #process
Risk-taking as a Learning Process for Shaping Teen’s Online Information Privacy Behaviors (HJ, PJW, HX, MBR, JMC), pp. 583–599.
HCIDHM-EH-2015-NakamuraKKMK #development #self #student #using
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.
HCIDHM-HM-2015-NishimuraK #case study #learning
A Study on Learning Effects of Marking with Highlighter Pen (HN, NK), pp. 357–367.
HCIDUXU-DD-2015-Fabri #design #education #lessons learnt #student
Thinking with a New Purpose: Lessons Learned from Teaching Design Thinking Skills to Creative Technology Students (MF), pp. 32–43.
HCIDUXU-DD-2015-KremerL #design #experience #learning #research #user interface
Learning from Experience Oriented Disciplines for User Experience Design — A Research Agenda (SK, UL), pp. 306–314.
HCIDUXU-DD-2015-Schneidermeier #lessons learnt #usability
Lessons Learned in Usability Consulting (TS), pp. 247–255.
HCIDUXU-IXD-2015-BorgesonFKTR #energy #learning #visualisation
Learning from Hourly Household Energy Consumption: Extracting, Visualizing and Interpreting Household Smart Meter Data (SB, JAF, JK, CWT, RR), pp. 337–345.
HCIDUXU-IXD-2015-BorumBB #design #learning #lessons learnt
Designing with Young Children: Lessons Learned from a Co-creation of a Technology-Enhanced Playful Learning Environment (NB, EPB, ALB), pp. 142–152.
HCIDUXU-IXD-2015-Celi #experience #learning #modelling #risk management #user interface
Application of Dashboards and Scorecards for Learning Models IT Risk Management: A User Experience (EC), pp. 153–165.
HCIDUXU-IXD-2015-Ovesleova #adaptation #concept #motivation #online #student #user interface
E-Learning Platforms and Lacking Motivation in Students: Concept of Adaptable UI for Online Courses (HO), pp. 218–227.
HCIDUXU-UI-2015-BeltranUPSSSPCA #design #game studies #learning
Inclusive Gaming Creation by Design in Formal Learning Environments: “Girly-Girls” User Group in No One Left Behind (MEB, YU, AP, CS, WS, BS, SdlRP, MFCU, MTA), pp. 153–161.
HCIHCI-DE-2015-BakkeB #developer #learning #proximity
The Closer the Better: Effects of Developer-User Proximity for Mutual Learning (SB, TB), pp. 14–26.
HCIHCI-IT-2015-TadayonMGRZLGP #case study #interactive #learning
Interactive Motor Learning with the Autonomous Training Assistant: A Case Study (RT, TLM, MG, PMRF, JZ, ML, MG, SP), pp. 495–506.
HCIHIMI-IKC-2015-AraiTA #development #learning
Development of a Learning Support System for Class Structure Mapping Based on Viewpoint (TA, TT, TA), pp. 285–293.
HCIHIMI-IKC-2015-HasegawaD #approach #framework #learning #ubiquitous
A Ubiquitous Lecture Archive Learning Platform with Note-Centered Approach (SH, JD), pp. 294–303.
HCIHIMI-IKC-2015-HayashiH #analysis #concept #learning #process
Analysis of the Relationship Between Metacognitive Ability and Learning Activity with Kit-Build Concept Map (YH, TH), pp. 304–312.
HCIHIMI-IKC-2015-Iwata #difference #learning
Method to Generate an Operation Learning Support System by Shortcut Key Differences in Similar Software (HI), pp. 332–340.
HCIHIMI-IKC-2015-KimitaMMNIS #education #learning
Learning State Model for Value Co-Creative Education Services (KK, KM, SM, YN, TI, YS), pp. 341–349.
HCIHIMI-IKC-2015-TogawaK #collaboration #framework #using
Disaster Recovery Framework for e-Learning Environment Using Private Cloud Collaboration and Emergency Alerts (ST, KK), pp. 588–596.
HCIHIMI-IKC-2015-WatanabeTA #abstraction #development #learning #source code
Development of a Learning Support System for Reading Source Code by Stepwise Abstraction (KW, TT, TA), pp. 387–394.
HCIHIMI-IKD-2015-WinterSTMCSVS #learning #question #student
Learning to Manage NextGen Environments: Do Student Controllers Prefer to Use Datalink or Voice? (AW, JS, YT, AM, SC, KS, KPLV, TZS), pp. 661–667.
HCILCT-2015-BoonbrahmKB #artificial reality #learning #student #using
Using Augmented Reality Technology in Assisting English Learning for Primary School Students (SB, CK, PB), pp. 24–32.
HCILCT-2015-DalipiYK #analysis #performance #semantics #using
Enhancing the Learner’s Performance Analysis Using SMEUS Semantic E-learning System and Business Intelligence Technologies (FD, SYY, ZK), pp. 208–217.
HCILCT-2015-DirinN #design #development #framework
Assessments of User Centered Design Framework for M-learning Application Development (AD, MN), pp. 62–74.
HCILCT-2015-DuA #artificial reality #design #evaluation #learning
Design and Evaluation of a Learning Assistant System with Optical Head-Mounted Display (OHMD) (XD, AA), pp. 75–86.
HCILCT-2015-FardounAC #education #evaluation
Creation of Meaningful-Learning and Continuous Evaluation Education System (HMF, AA, APC), pp. 218–226.
HCILCT-2015-FardounAC15a #self #student
Construction of Educative Micro-Worlds to Build Students’ Creativity in Terms of Their Own Self-Learning (HMF, AAMAG, APC), pp. 349–360.
HCILCT-2015-FonsecaRVG #3d #education #learning
From Formal to Informal 3D Learning. Assesment of Users in the Education (DF, ER, FV, ODG), pp. 460–469.
HCILCT-2015-GoelMTPSYD #collaboration #learning #named #student
CATALYST: Technology-Assisted Collaborative and Experiential Learning for School Students (VG, UM, ST, RMP, KS, KY, OD), pp. 482–491.
HCILCT-2015-GonzalezHGS #interactive #learning #student #tool support
Exploring Student Interactions: Learning Analytics Tools for Student Tracking (MÁCG, ÁHG, FJGP, MLSE), pp. 50–61.
HCILCT-2015-HoffmannPLSMJ #learning #student
Enhancing the Learning Success of Engineering Students by Virtual Experiments (MH, LP, LL, KS, TM, SJ), pp. 394–405.
HCILCT-2015-KimAKW #game studies #learning
H-Treasure Hunt: A Location and Object-Based Serious Game for Cultural Heritage Learning at a Historic Site (HK, SA, SK, WW), pp. 561–572.
HCILCT-2015-KimCD #artificial reality #learning #simulation
The Learning Effect of Augmented Reality Training in a Computer-Based Simulation Environment (JHK, TC, WD), pp. 406–414.
HCILCT-2015-KlemkeKLS #education #game studies #learning #mobile #multi
Transferring an Educational Board Game to a Multi-user Mobile Learning Game to Increase Shared Situational Awareness (RK, SK, HL, MS), pp. 583–594.
HCILCT-2015-KlockCCRAG #adaptation #concept #gamification #student
Gamification in e-Learning Systems: A Conceptual Model to Engage Students and Its Application in an Adaptive e-Learning System (ACTK, LFDC, MFdC, BER, AJA, IG), pp. 595–607.
HCILCT-2015-LambropoulosMFK #design #experience #learning #ontology
Ontological Design to Support Cognitive Plasticity for Creative Immersive Experience in Computer Aided Learning (NL, IM, HMF, IAK), pp. 261–270.
HCILCT-2015-OrehovackiB #game studies #learning #programming #quality
Inspecting Quality of Games Designed for Learning Programming (TO, SB), pp. 620–631.
HCILCT-2015-RodriguezOD #hybrid #learning #recommendation #repository #student
A Student-Centered Hybrid Recommender System to Provide Relevant Learning Objects from Repositories (PAR, DAO, NDD), pp. 291–300.
HCILCT-2015-ShimizuO #design #implementation #learning #novel #word
Design and Implementation of Novel Word Learning System “Überall” (RS, KO), pp. 148–159.
HCILCT-2015-TamuraTHN #generative #learning #wiki
Generating Quizzes for History Learning Based on Wikipedia Articles (YT, YT, YH, YIN), pp. 337–346.
HCILCT-2015-VallsRF #architecture #design #education #game studies #roadmap
E-Learning and Serious Games — New Trends in Architectural and Urban Design Education (FV, ER, DF), pp. 632–643.
HCILCT-2015-VielRTP #design #interactive #learning #multi
Design Solutions for Interactive Multi-video Multimedia Learning Objects (CCV, KRHR, CACT, MdGCP), pp. 160–171.
HCILCT-2015-YusoffK #design #game studies #interactive #learning #persuasion
Game Rhetoric: Interaction Design Model of Persuasive Learning for Serious Games (ZY, AK), pp. 644–654.
ICEISICEIS-v1-2015-PecliGPMFTTDFCG #learning #predict #problem #reduction
Dimensionality Reduction for Supervised Learning in Link Prediction Problems (AP, BG, CCP, CM, FF, FT, JT, MVD, SF, MCC, RRG), pp. 295–302.
ICEISICEIS-v1-2015-RibeiroTWBE #learning
A Learning Model for Intelligent Agents Applied to Poultry Farming (RR, MT, ALW, APB, FE), pp. 495–503.
ICEISICEIS-v1-2015-SouzaBGBE #learning #online
Applying Ensemble-based Online Learning Techniques on Crime Forecasting (AJdS, APB, HMG, JPB, FE), pp. 17–24.
ICEISICEIS-v2-2015-Judrups #analysis #information management #integration
Analysis of Knowledge Management and E-Learning Integration Approaches (JJ), pp. 451–456.
ECIRECIR-2015-HuynhHR #analysis #learning #sentiment #strict
Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis (TH, YH, SMR), pp. 447–452.
ECIRECIR-2015-KingI #clustering #generative #music
Generating Music Playlists with Hierarchical Clustering and Q-Learning (JK, VI), pp. 315–326.
ECIRECIR-2015-LiHLZ #twitter
Selecting Training Data for Learning-Based Twitter Search (DL, BH, TL, XZ), pp. 501–506.
ECIRECIR-2015-NicosiaBM #learning #rank
Learning to Rank Aggregated Answers for Crossword Puzzles (MN, GB, AM), pp. 556–561.
ECIRECIR-2015-PasinatoMZ #elicitation #learning #rating
Active Learning Applied to Rating Elicitation for Incentive Purposes (MBP, CEM, GZ), pp. 291–302.
ECIRECIR-2015-PelejaM #learning #retrieval #sentiment
Learning Sentiment Based Ranked-Lexicons for Opinion Retrieval (FP, JM), pp. 435–440.
ICMLICML-2015-AmidU #learning #multi
Multiview Triplet Embedding: Learning Attributes in Multiple Maps (EA, AU), pp. 1472–1480.
ICMLICML-2015-BachHBG #learning #performance
Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs (SHB, BH, JLBG, LG), pp. 381–390.
ICMLICML-2015-BlumH #contest #machine learning #reliability
The Ladder: A Reliable Leaderboard for Machine Learning Competitions (AB, MH), pp. 1006–1014.
ICMLICML-2015-Bou-AmmarTE #learning #policy #sublinear
Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret (HBA, RT, EE), pp. 2361–2369.
ICMLICML-2015-ChangKADL #education #learning
Learning to Search Better than Your Teacher (KWC, AK, AA, HDI, JL), pp. 2058–2066.
ICMLICML-2015-ChenSYU #learning #modelling
Learning Deep Structured Models (LCC, AGS, ALY, RU), pp. 1785–1794.
ICMLICML-2015-CilibertoMPR #learning #multi
Convex Learning of Multiple Tasks and their Structure (CC, YM, TAP, LR), pp. 1548–1557.
ICMLICML-2015-CohenH #learning #online
Following the Perturbed Leader for Online Structured Learning (AC, TH), pp. 1034–1042.
ICMLICML-2015-DanielyGS #adaptation #learning #online
Strongly Adaptive Online Learning (AD, AG, SSS), pp. 1405–1411.
ICMLICML-2015-FetayaU #invariant #learning
Learning Local Invariant Mahalanobis Distances (EF, SU), pp. 162–168.
ICMLICML-2015-GarberHM #learning #online
Online Learning of Eigenvectors (DG, EH, TM), pp. 560–568.
ICMLICML-2015-GuptaAGN #learning #precise
Deep Learning with Limited Numerical Precision (SG, AA, KG, PN), pp. 1737–1746.
ICMLICML-2015-HallakSMM #learning #modelling
Off-policy Model-based Learning under Unknown Factored Dynamics (AH, FS, TAM, SM), pp. 711–719.
ICMLICML-2015-Hernandez-Lobato15b #learning #network #probability #scalability
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks (JMHL, RA), pp. 1861–1869.
ICMLICML-2015-HockingRB #detection #learning #named #segmentation
PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data (TH, GR, GB), pp. 324–332.
ICMLICML-2015-HongYKH #learning #network #online
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network (SH, TY, SK, BH), pp. 597–606.
ICMLICML-2015-HsiehND #learning #matrix
PU Learning for Matrix Completion (CJH, NN, ISD), pp. 2445–2453.
ICMLICML-2015-HuangWSLC #classification #image #learning #metric #set #symmetry
Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification (ZH, RW, SS, XL, XC), pp. 720–729.
ICMLICML-2015-JerniteRS #approach #learning #markov #modelling #performance #random
A Fast Variational Approach for Learning Markov Random Field Language Models (YJ, AMR, DS), pp. 2209–2217.
ICMLICML-2015-JiangKS #abstraction #learning #modelling
Abstraction Selection in Model-based Reinforcement Learning (NJ, AK, SS), pp. 179–188.
ICMLICML-2015-Kandemir #learning #process #symmetry
Asymmetric Transfer Learning with Deep Gaussian Processes (MK), pp. 730–738.
ICMLICML-2015-KvetonSWA #learning #rank
Cascading Bandits: Learning to Rank in the Cascade Model (BK, CS, ZW, AA), pp. 767–776.
ICMLICML-2015-LakshmananOR #bound #learning
Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning (KL, RO, DR), pp. 524–532.
ICMLICML-2015-LeC #learning #metric #using
Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations (TL, MC), pp. 2002–2011.
ICMLICML-2015-LiuY #graph #learning #predict
Bipartite Edge Prediction via Transductive Learning over Product Graphs (HL, YY), pp. 1880–1888.
ICMLICML-2015-LondonHG #approximate #learning
The Benefits of Learning with Strongly Convex Approximate Inference (BL, BH, LG), pp. 410–418.
ICMLICML-2015-LongC0J #adaptation #learning #network
Learning Transferable Features with Deep Adaptation Networks (ML, YC, JW, MJ), pp. 97–105.
ICMLICML-2015-Lopez-PazMST #learning #towards
Towards a Learning Theory of Cause-Effect Inference (DLP, KM, BS, IT), pp. 1452–1461.
ICMLICML-2015-MaclaurinDA #learning #optimisation
Gradient-based Hyperparameter Optimization through Reversible Learning (DM, DKD, RPA), pp. 2113–2122.
ICMLICML-2015-MarietS #algorithm #fixpoint #learning #process
Fixed-point algorithms for learning determinantal point processes (ZM, SS), pp. 2389–2397.
ICMLICML-2015-MenonROW #estimation #learning
Learning from Corrupted Binary Labels via Class-Probability Estimation (AKM, BvR, CSO, BW), pp. 125–134.
ICMLICML-2015-PerrotH #analysis #learning #metric
A Theoretical Analysis of Metric Hypothesis Transfer Learning (MP, AH), pp. 1708–1717.
ICMLICML-2015-PhamRFA #learning #multi #novel
Multi-instance multi-label learning in the presence of novel class instances (ATP, RR, XZF, JPA), pp. 2427–2435.
ICMLICML-2015-PiechHNPSG #feedback #learning #student
Learning Program Embeddings to Propagate Feedback on Student Code (CP, JH, AN, MP, MS, LJG), pp. 1093–1102.
ICMLICML-2015-PlessisNS #learning
Convex Formulation for Learning from Positive and Unlabeled Data (MCdP, GN, MS), pp. 1386–1394.
ICMLICML-2015-Romera-ParedesT #approach #learning
An embarrassingly simple approach to zero-shot learning (BRP, PHST), pp. 2152–2161.
ICMLICML-2015-SerrurierP #evaluation #learning
Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees (MS, HP), pp. 1576–1584.
ICMLICML-2015-SibonyCJ #learning #ranking #statistics
MRA-based Statistical Learning from Incomplete Rankings (ES, SC, JJ), pp. 1432–1441.
ICMLICML-2015-Sohl-DicksteinW #learning #using
Deep Unsupervised Learning using Nonequilibrium Thermodynamics (JSD, EAW, NM, SG), pp. 2256–2265.
ICMLICML-2015-SrivastavaMS #learning #using #video
Unsupervised Learning of Video Representations using LSTMs (NS, EM, RS), pp. 843–852.
ICMLICML-2015-SteinhardtL15a #learning #modelling #predict
Learning Fast-Mixing Models for Structured Prediction (JS, PL), pp. 1063–1072.
ICMLICML-2015-SwaminathanJ #feedback #learning
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback (AS, TJ), pp. 814–823.
ICMLICML-2015-TangSX #learning #network
Learning Scale-Free Networks by Dynamic Node Specific Degree Prior (QT, SS, JX), pp. 2247–2255.
ICMLICML-2015-TewariC #bound #documentation #fault #learning #matter #question #rank
Generalization error bounds for learning to rank: Does the length of document lists matter? (AT, SC), pp. 315–323.
ICMLICML-2015-VanseijenS #learning
A Deeper Look at Planning as Learning from Replay (HV, RS), pp. 2314–2322.
ICMLICML-2015-WangALB #learning #multi #on the #representation
On Deep Multi-View Representation Learning (WW, RA, KL, JAB), pp. 1083–1092.
ICMLICML-2015-WangWLCW #learning #multi #segmentation
Multi-Task Learning for Subspace Segmentation (YW, DPW, QL, WC, IJW), pp. 1209–1217.
ICMLICML-2015-WangY #learning #matrix #multi
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices (JW, JY), pp. 1747–1756.
ICMLICML-2015-WeiIB #learning #set
Submodularity in Data Subset Selection and Active Learning (KW, RKI, JAB), pp. 1954–1963.
ICMLICML-2015-WeissN #alias #learning
Learning Parametric-Output HMMs with Two Aliased States (RW, BN), pp. 635–644.
ICMLICML-2015-WenKA #combinator #learning #performance #scalability
Efficient Learning in Large-Scale Combinatorial Semi-Bandits (ZW, BK, AA), pp. 1113–1122.
ICMLICML-2015-WuS #algorithm #learning #modelling #online
An Online Learning Algorithm for Bilinear Models (YW, SS), pp. 890–898.
ICMLICML-2015-YogatamaFDS #learning #word
Learning Word Representations with Hierarchical Sparse Coding (DY, MF, CD, NAS), pp. 87–96.
ICMLICML-2015-YuB #learning
Learning Submodular Losses with the Lovasz Hinge (JY, MBB), pp. 1623–1631.
ICMLICML-2015-YuCL #learning #multi #online #rank
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams (RY, DC, YL), pp. 238–247.
KDDKDD-2015-Agarwal #machine learning #scalability #statistics #web
Scaling Machine Learning and Statistics for Web Applications (DA), p. 1621.
KDDKDD-2015-Athey #evaluation #machine learning #policy
Machine Learning and Causal Inference for Policy Evaluation (SA), pp. 5–6.
KDDKDD-2015-ChakrabortyBSPY #classification #framework #learning #named #novel
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification (SC, VNB, ARS, SP, JY), pp. 99–108.
KDDKDD-2015-Durrant-Whyte #machine learning
Data, Knowledge and Discovery: Machine Learning meets Natural Science (HDW), p. 7.
KDDKDD-2015-DuS #adaptation #feature model #learning
Unsupervised Feature Selection with Adaptive Structure Learning (LD, YDS), pp. 209–218.
KDDKDD-2015-GaoYCH #integration #learning #multi #visual notation
Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration: Multi-Dimensional Feature Learning (HG, LY, WC, HH), pp. 339–348.
KDDKDD-2015-GleichM #algorithm #graph #learning #using
Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms (DFG, MWM), pp. 359–368.
KDDKDD-2015-Gomez-Rodriguez #machine learning #modelling #network #probability #problem #research #social
Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods (MGR, LS), pp. 2315–2316.
KDDKDD-2015-HanZ #learning #multi
Learning Tree Structure in Multi-Task Learning (LH, YZ), pp. 397–406.
KDDKDD-2015-JohanssonD #geometry #graph #learning #similarity #using
Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings (FDJ, DPD), pp. 467–476.
KDDKDD-2015-Koller #named #question #what
MOOCS: What Have We Learned? (DK), p. 3.
KDDKDD-2015-LakkarajuASMBGA #framework #identification #machine learning #student
A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes (HL, EA, CS, DM, NB, RG, KLA), pp. 1909–1918.
KDDKDD-2015-LanH #complexity #learning #multi
Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning (CL, JH), pp. 627–634.
KDDKDD-2015-LinLC #framework #multi #network #social
A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks (SCL, SDL, MSC), pp. 695–704.
KDDKDD-2015-MaoWGS #graph #learning #reduction
Dimensionality Reduction Via Graph Structure Learning (QM, LW, SG, YS), pp. 765–774.
KDDKDD-2015-NairRKBSKHD #detection #learning #monitoring
Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues (VN, AR, SK, VB, SS, SSK, SH, SD), pp. 2029–2038.
KDDKDD-2015-Papagiannopoulou #learning #multi
Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning (CP, GT, IT), pp. 915–924.
KDDKDD-2015-Pratt #machine learning #predict #protocol #proving
Proof Protocol for a Machine Learning Technique Making Longitudinal Predictions in Dynamic Contexts (KBP), pp. 2049–2058.
KDDKDD-2015-RiondatoU15a #algorithm #learning #statistics
VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms (MR, EU), pp. 2321–2322.
KDDKDD-2015-Schleier-Smith #agile #architecture #machine learning #realtime
An Architecture for Agile Machine Learning in Real-Time Applications (JSS), pp. 2059–2068.
KDDKDD-2015-SethiYRVR #classification #machine learning #scalability #using
Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery (MS, YY, AR, RRV, SR), pp. 2069–2078.
KDDKDD-2015-ShashidharPA #machine learning
Spoken English Grading: Machine Learning with Crowd Intelligence (VS, NP, VA), pp. 2089–2097.
KDDKDD-2015-SunAYMMBY #classification #learning
Transfer Learning for Bilingual Content Classification (QS, MSA, BY, CM, VM, AB, JY), pp. 2147–2156.
KDDKDD-2015-TanSZ0 #learning #transitive
Transitive Transfer Learning (BT, YS, EZ, QY), pp. 1155–1164.
KDDKDD-2015-VeeriahDQ #architecture #learning #predict
Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction (VV, RD, GJQ), pp. 1205–1214.
KDDKDD-2015-WangWY #collaboration #learning #recommendation
Collaborative Deep Learning for Recommender Systems (HW, NW, DYY), pp. 1235–1244.
KDDKDD-2015-XingHDKWLZXKY #big data #distributed #framework #machine learning #named
Petuum: A New Platform for Distributed Machine Learning on Big Data (EPX, QH, WD, JKK, JW, SL, XZ, PX, AK, YY), pp. 1335–1344.
KDDKDD-2015-XuSB #learning #predict
Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction (TX, JS, JB), pp. 1345–1354.
KDDKDD-2015-YangH #learning #multi
Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning (PY, JH), pp. 1375–1384.
KDDKDD-2015-YangSJWDY #learning #visual notation
Structural Graphical Lasso for Learning Mouse Brain Connectivity (SY, QS, SJ, PW, ID, JY), pp. 1385–1394.
KDDKDD-2015-YanRHC #distributed #learning #modelling #optimisation #performance #scalability
Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems (FY, OR, YH, TMC), pp. 1355–1364.
KDDKDD-2015-ZhangLZSKYJ #analysis #biology #image #learning #modelling #multi
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis (WZ, RL, TZ, QS, SK, JY, SJ), pp. 1475–1484.
KDDKDD-2015-ZhaoSYCLR #learning #multi
Multi-Task Learning for Spatio-Temporal Event Forecasting (LZ, QS, JY, FC, CTL, NR), pp. 1503–1512.
MLDMMLDM-2015-Chou #data-driven #geometry #learning
Data Driven Geometry for Learning (EPC), pp. 395–402.
MLDMMLDM-2015-DhulekarNOY #graph #learning #mining #predict
Seizure Prediction by Graph Mining, Transfer Learning, and Transformation Learning (ND, SN, BO, BY), pp. 32–52.
MLDMMLDM-2015-FerrerSR #approximate #distance #edit distance #graph #heuristic #learning
Learning Heuristics to Reduce the Overestimation of Bipartite Graph Edit Distance Approximation (MF, FS, KR), pp. 17–31.
MLDMMLDM-2015-GovadaJMS #approach #hybrid #induction #learning #using
Hybrid Approach for Inductive Semi Supervised Learning Using Label Propagation and Support Vector Machine (AG, PJ, SM, SKS), pp. 199–213.
MLDMMLDM-2015-KrasotkinaM #approach #optimisation #ranking
A Bayesian Approach to Sparse Learning-to-Rank for Search Engine Optimization (OK, VM), pp. 382–394.
MLDMMLDM-2015-MoldovanM #data mining #learning #mining #performance #using
Learning the Relationship Between Corporate Governance and Company Performance Using Data Mining (DM, SM), pp. 368–381.
RecSysRecSys-2015-AlmahairiKCC #collaboration #distributed #learning
Learning Distributed Representations from Reviews for Collaborative Filtering (AA, KK, KC, ACC), pp. 147–154.
RecSysRecSys-2015-HuD #machine learning #recommendation #scalability
Scalable Recommender Systems: Where Machine Learning Meets Search (SYDH, JD), pp. 365–366.
RecSysRecSys-2015-SongCL #incremental #matrix #recommendation
Incremental Matrix Factorization via Feature Space Re-learning for Recommender System (QS, JC, HL), pp. 277–280.
SEKESEKE-2015-AffonsoLON #adaptation #framework #learning #self
A Framework Based on Learning Techniques for Decision-making in Self-adaptive Software (FJA, GL, RAPO, EYN), pp. 24–29.
SEKESEKE-2015-GoswamiWS #learning #performance #using
Using Learning Styles of Software Professionals to Improve their Inspection Team Performance (AG, GSW, AS), pp. 680–685.
SEKESEKE-2015-LiuXC #learning #recommendation
Context-aware Recommendation System with Anonymous User Profile Learning (YL, YX, MC), pp. 93–98.
SEKESEKE-2015-Murillo-MoreraJ #algorithm #approach #framework #learning #predict #search-based #using
A Software Defect-Proneness Prediction Framework: A new approach using genetic algorithms to generate learning schemes (JMM, MJ), pp. 445–450.
SEKESEKE-2015-SampaioMLM #adaptation #approach #learning #research
Reflecting, adapting and learning in small software organizations: an action research approach (SS, MM, AL, HPM), pp. 46–50.
SEKESEKE-2015-SaputriL #analysis #machine learning #perspective
Are We Living in a Happy Country: An Analysis of National Happiness from Machine Learning Perspective (TRDS, SWL), pp. 174–177.
SEKESEKE-2015-TironiMRM #approach #identification #learning
An approach to identify relevant subjects for supporting the Learning Scheme creation task (HT, ALAM, SSR, AM), pp. 506–511.
SEKESEKE-2015-WanderleyP #detection #folksonomy #learning
Learning Folksonomies for Trend Detection in Task-Oriented Dialogues (GW, ECP), pp. 483–488.
SEKESEKE-2015-ZegarraCW #graph #learning #visualisation
Facilitating Peer Learning and Knowledge Sharing in STEM Courses via Pattern Based Graph Visualization (EZ, SKC, JW), pp. 284–289.
SIGIRSIGIR-2015-Arora #learning
Promoting User Engagement and Learning in Amorphous Search Tasks (PA), p. 1051.
SIGIRSIGIR-2015-CormackG #bibliography #learning #multi #perspective
Multi-Faceted Recall of Continuous Active Learning for Technology-Assisted Review (GVC, MRG), pp. 763–766.
SIGIRSIGIR-2015-FoleyBJ #learning #web
Learning to Extract Local Events from the Web (JF, MB, VJ), pp. 423–432.
SIGIRSIGIR-2015-HarveyHE #learning #query
Learning by Example: Training Users with High-quality Query Suggestions (MH, CH, DE), pp. 133–142.
SIGIRSIGIR-2015-Li15a #information retrieval #learning
Transfer Learning for Information Retrieval (PL), p. 1061.
SIGIRSIGIR-2015-LiuW #collaboration #learning
Learning Context-aware Latent Representations for Context-aware Collaborative Filtering (XL, WW), pp. 887–890.
SIGIRSIGIR-2015-MehrotraY #learning #query #rank #using
Representative & Informative Query Selection for Learning to Rank using Submodular Functions (RM, EY), pp. 545–554.
SIGIRSIGIR-2015-SeverynM #learning #network #rank
Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks (AS, AM), pp. 373–382.
SIGIRSIGIR-2015-SongNZAC #learning #multi #network #predict #social #volunteer
Multiple Social Network Learning and Its Application in Volunteerism Tendency Prediction (XS, LN, LZ, MA, TSC), pp. 213–222.
SIGIRSIGIR-2015-SpinaPR #learning #microblog
Active Learning for Entity Filtering in Microblog Streams (DS, MHP, MdR), pp. 975–978.
SIGIRSIGIR-2015-WangGLXWC #learning #recommendation #representation
Learning Hierarchical Representation Model for NextBasket Recommendation (PW, JG, YL, JX, SW, XC), pp. 403–412.
SIGIRSIGIR-2015-WangLWZZ #learning #named
LBMCH: Learning Bridging Mapping for Cross-modal Hashing (YW, XL, LW, WZ, QZ), pp. 999–1002.
SIGIRSIGIR-2015-XiaXLGC #evaluation #learning #metric #optimisation
Learning Maximal Marginal Relevance Model via Directly Optimizing Diversity Evaluation Measures (LX, JX, YL, JG, XC), pp. 113–122.
SIGIRSIGIR-2015-ZamaniMS #adaptation #evaluation #learning #multi
Adaptive User Engagement Evaluation via Multi-task Learning (HZ, PM, AS), pp. 1011–1014.
SIGIRSIGIR-2015-ZhengC #distributed #learning
Learning to Reweight Terms with Distributed Representations (GZ, JC), pp. 575–584.
MoDELSMoDELS-2015-HajriGBS #approach #case study #embedded #industrial #lessons learnt #modelling #product line
Applying product line Use case modeling in an industrial automotive embedded system: Lessons learned and a refined approach (IH, AG, LCB, TS), pp. 338–347.
MoDELSMoDELS-2015-LettnerEGP #case study #experience #feature model #industrial #lessons learnt #modelling #scalability
Feature modeling of two large-scale industrial software systems: Experiences and lessons learned (DL, KE, PG, HP), pp. 386–395.
OOPSLAOOPSLA-2015-OhYY #adaptation #learning #optimisation #program analysis
Learning a strategy for adapting a program analysis via bayesian optimisation (HO, HY, KY), pp. 572–588.
SACSAC-2015-BarrosCMP #education #learning #repository #reuse
Integrating educational repositories to improve the reuse of learning objects (HB, EC, JM, RP), pp. 270–272.
SACSAC-2015-Brefeld #learning #multi
Multi-view learning with dependent views (UB), pp. 865–870.
SACSAC-2015-CruzPQSSOBO #algorithm #game studies #named #probability #using
Amê: an environment to learn and analyze adversarial search algorithms using stochastic card games (ABC, LP, JQ, US, SS, AO, EB, ESO), pp. 208–213.
SACSAC-2015-FauconnierKR #approach #machine learning #recognition #taxonomy
A supervised machine learning approach for taxonomic relation recognition through non-linear enumerative structures (JPF, MK, BR), pp. 423–425.
SACSAC-2015-GomesBE #classification #data type #learning
Pairwise combination of classifiers for ensemble learning on data streams (HMG, JPB, FE), pp. 941–946.
SACSAC-2015-JeongYAYP #algorithm #interactive #network #search-based #using
Inference of disease-specific gene interaction network using a Bayesian network learned by genetic algorithm (DJ, YY, JA, YY, SP), pp. 47–53.
SACSAC-2015-LabibPCG #approach #development #learning #product line #reuse
Enforcing reuse and customization in the development of learning objects: a product line approach (AEL, MCP, JHC, AG), pp. 261–263.
SACSAC-2015-NascimentoPM #algorithm #machine learning #metaheuristic
A data quality-aware cloud service based on metaheuristic and machine learning provisioning algorithms (DCN, CESP, DGM), pp. 1696–1703.
SACSAC-2015-OmatuYI #classification #learning #smell
Smell classification of wines by the learning vector quantization method (SO, MY, YI), pp. 195–200.
SACSAC-2015-PaivaBSIJ #behaviour #learning #recommendation #student
Improving pedagogical recommendations by classifying students according to their interactional behavior in a gamified learning environment (ROAP, IIB, APdS, SI, PAJ), pp. 233–238.
SACSAC-2015-PedroLPVI #case study #gamification #learning #women
Does gamification work for boys and girls?: An exploratory study with a virtual learning environment (LZP, AMZL, BGP, JV, SI), pp. 214–219.
SACSAC-2015-Pesare #learning #social
Smart learning environments for social learning (EP), pp. 273–274.
SACSAC-2015-ReadPB #data type #learning
Deep learning in partially-labeled data streams (JR, FPC, AB), pp. 954–959.
SACSAC-2015-ReddySC #approach #aspect-oriented #incremental #learning #performance #weaving
Incremental aspect weaving: an approach for faster AOP learning (YRR, AS, MC), pp. 1480–1485.
SACSAC-2015-RegoMP #approach #detection #folksonomy #learning
A supervised learning approach to detect subsumption relations between tags in folksonomies (ASdCR, LBM, CESP), pp. 409–415.
SACSAC-2015-StracciaM #concept #estimation #fuzzy #learning #named #owl #probability #using
pFOIL-DL: learning (fuzzy) EL concept descriptions from crisp OWL data using a probabilistic ensemble estimation (US, MM), pp. 345–352.
SACSAC-2015-SugiyamaS #learning #multi
Meta-strategy for cooperative tasks with learning of environments in multi-agent continuous tasks (AS, TS), pp. 494–500.
SACSAC-2015-WanderleyP #folksonomy #learning
Learning folksonomies from task-oriented dialogues (GMPW, ECP), pp. 360–367.
ESEC-FSEESEC-FSE-2015-JingWDQX #fault #learning #metric #predict #representation
Heterogeneous cross-company defect prediction by unified metric representation and CCA-based transfer learning (XYJ, FW, XD, FQ, BX), pp. 496–507.
ESEC-FSEESEC-FSE-2015-KoskiM #architecture #lessons learnt #quality #requirements
Requirements, architecture, and quality in a mission critical system: 12 lessons learned (AK, TM), pp. 1018–1021.
ESEC-FSEESEC-FSE-2015-SunXLLQ #abstraction #learning #named #testing #validation
TLV: abstraction through testing, learning, and validation (JS, HX, YL, SWL, SQ), pp. 698–709.
ICSEICSE-v1-2015-FilieriGL #adaptation #learning #lightweight #modelling #performance #probability
Lightweight Adaptive Filtering for Efficient Learning and Updating of Probabilistic Models (AF, LG, AL), pp. 200–211.
ICSEICSE-v1-2015-JiaCHP #combinator #generative #interactive #learning #testing #using
Learning Combinatorial Interaction Test Generation Strategies Using Hyperheuristic Search (YJ, MBC, MH, JP), pp. 540–550.
ICSEICSE-v1-2015-ZhuHFZLZ #developer #learning
Learning to Log: Helping Developers Make Informed Logging Decisions (JZ, PH, QF, HZ, MRL, DZ), pp. 415–425.
ICSEICSE-v2-2015-Hanakawa #contest #learning #motivation #re-engineering #student
Contest Based Learning with Blending Software Engineering and Business Management: For Students’ High Motivation and High Practice Ability (NH), pp. 360–369.
ICSEICSE-v2-2015-Honsel #evolution #learning #mining #simulation #statistics
Statistical Learning and Software Mining for Agent Based Simulation of Software Evolution (VH), pp. 863–866.
ICSEICSE-v2-2015-JankeBW #education #learning #object-oriented #programming #question
Does Outside-In Teaching Improve the Learning of Object-Oriented Programming? (EJ, PB, SW), pp. 408–417.
ICSEICSE-v2-2015-Jazayeri #case study #experience #learning #programming
Combining Mastery Learning with Project-Based Learning in a First Programming Course: An Experience Report (MJ), pp. 315–318.
ICSEICSE-v2-2015-MonsalveLW #education #game studies #learning
Transparently Teaching in the Context of Game-based Learning: the Case of SimulES-W (ESM, JCSdPL, VMBW), pp. 343–352.
ICSEICSE-v2-2015-PaasivaaraBLDSH #agile #learning #re-engineering #using
Learning Global Agile Software Engineering Using Same-Site and Cross-Site Teams (MP, KB, CL, DED, JS, FH, PC, AY, VI), pp. 285–294.
ICSEICSE-v2-2015-SedelmaierL #education #induction #learning #re-engineering
Active and Inductive Learning in Software Engineering Education (YS, DL), pp. 418–427.
ICSEICSE-v2-2015-SoundarajanJR #collaboration #re-engineering
Collaborative and Cooperative-Learning in Software Engineering Courses (NS, SJ, RR), pp. 319–322.
ICSEICSE-v2-2015-WilkinsG #design #learning #student
Drawing Insight from Student Perceptions of Reflective Design Learning (TVW, JCG), pp. 253–262.
ASPLOSASPLOS-2015-LiuCLZZTFZC #machine learning #named
PuDianNao: A Polyvalent Machine Learning Accelerator (DFL, TC, SL, JZ, SZ, OT, XF, XZ, YC), pp. 369–381.
CGOCGO-2015-McAfeeO #framework #generative #learning #multi #named
EMEURO: a framework for generating multi-purpose accelerators via deep learning (LCM, KO), pp. 125–135.
HPCAHPCA-2015-WuGLJC #estimation #machine learning #performance #using
GPGPU performance and power estimation using machine learning (GYW, JLG, AL, NJ, DC), pp. 564–576.
PPoPPPPoPP-2015-AshariTBRCKS #kernel #machine learning #on the #optimisation
On optimizing machine learning workloads via kernel fusion (AA, ST, MB, BR, KC, JK, PS), pp. 173–182.
CAVCAV-2015-BrazdilCCFK #learning #markov #process
Counterexample Explanation by Learning Small Strategies in Markov Decision Processes (TB, KC, MC, AF, JK), pp. 158–177.
CAVCAV-2015-GehrDV #commutative #learning #specification
Learning Commutativity Specifications (TG, DD, MTV), pp. 307–323.
CAVCAV-2015-IsbernerHS #automaton #framework #learning #open source
The Open-Source LearnLib — A Framework for Active Automata Learning (MI, FH, BS), pp. 487–495.
CAVCAV-2015-Saha0M #learning #named
Alchemist: Learning Guarded Affine Functions (SS, PG, PM), pp. 440–446.
ICLPICLP-2015-MartinezRIAT #learning #modelling #probability
Learning Probabilistic Action Models from Interpretation Transitions (DM, TR, KI, GA, CT).
ICLPICLP-J-2015-LawRB #constraints #learning #programming #set
Learning weak constraints in answer set programming (ML, AR, KB), pp. 511–525.
ICSTSAT-2015-TuHJ #learning #named #reasoning #satisfiability
QELL: QBF Reasoning with Extended Clause Learning and Levelized SAT Solving (KHT, TCH, JHRJ), pp. 343–359.
WICSAWICSA-2014-UusitaloRKMM #architecture #automation #lessons learnt #safety
Lessons Learned from Safety-Critical Software-Based Automation Architectures of Nuclear Power Plants (EJU, MR, MK, VM, TM), pp. 45–48.
ASEASE-2014-NguyenNNN #api #approach #learning #migration #mining #statistics
Statistical learning approach for mining API usage mappings for code migration (ATN, HAN, TTN, TNN), pp. 457–468.
CASECASE-2014-HabibDBHP #android #learning
Learning human-like facial expressions for Android Phillip K. Dick (AH, SKD, ICB, DH, DOP), pp. 1159–1165.
CASECASE-2014-HwangLW #adaptation #learning
Adaptive reinforcement learning in box-pushing robots (KSH, JLL, WHW), pp. 1182–1187.
CASECASE-2014-KernWGBM #estimation #machine learning #using
COD and NH4-N estimation in the inflow of Wastewater Treatment Plants using Machine Learning Techniques (PK, CW, DG, MB, SFM), pp. 812–817.
CASECASE-2014-MaDLZ #learning #modelling #simulation
Modeling and simulation of product diffusion considering learning effect (KPM, XD, CFL, JZ), pp. 665–670.
CASECASE-2014-MahlerKLSMKPWFAG #learning #process #using
Learning accurate kinematic control of cable-driven surgical robots using data cleaning and Gaussian Process Regression (JM, SK, ML, SS, AM, BK, SP, JW, MF, PA, KYG), pp. 532–539.
CASECASE-2014-MinakaisMW #learning
Groundhog Day: Iterative learning for building temperature control (MM, SM, JTW), pp. 948–953.
CASECASE-2014-MurookaNNKOI #learning #physics #scalability
Manipulation strategy learning for carrying large objects based on mapping from object physical property to object manipulation action in virtual environment (MM, SN, SN, YK, KO, MI), pp. 263–270.
CASECASE-2014-SustoWPZJOM #adaptation #flexibility #machine learning #maintenance #predict
An adaptive machine learning decision system for flexible predictive maintenance (GAS, JW, SP, MZ, ABJ, PGO, SFM), pp. 806–811.
DACDAC-2014-0001SMAKV #manycore #optimisation
Reinforcement Learning-Based Inter- and Intra-Application Thermal Optimization for Lifetime Improvement of Multicore Systems (AD, RAS, GVM, BMAH, AK, BV), p. 6.
DACDAC-2014-AlbalawiLL #algorithm #classification #design #fixpoint #implementation #machine learning #power management
Computer-Aided Design of Machine Learning Algorithm: Training Fixed-Point Classifier for On-Chip Low-Power Implementation (HA, YL, XL), p. 6.
DACDAC-2014-FarkashHB #incremental #validation
Coverage Learned Targeted Validation for Incremental HW Changes (MF, BGH, MB), p. 6.
DATEDATE-2014-HanKNV #learning
A deep learning methodology to proliferate golden signoff timing (SSH, ABK, SN, ASV), pp. 1–6.
DATEDATE-2014-XuB #hybrid #question
Hybrid side-channel/machine-learning attacks on PUFs: A new threat? (XX, WB), pp. 1–6.
DRRDRR-2014-CartonLC #interactive #learning #named
LearnPos: a new tool for interactive learning positioning (CC, AL, BC), p. ?–12.
DRRDRR-2014-MaXA #algorithm #machine learning #segmentation #video
A machine learning based lecture video segmentation and indexing algorithm (DM, BX, GA), p. ?–8.
DRRDRR-2014-TaoTX #documentation #learning #random #using
Document page structure learning for fixed-layout e-books using conditional random fields (XT, ZT, CX), p. ?–9.
HTHT-2014-AbbasiTL #learning #scalability #using
Scalable learning of users’ preferences using networked data (MAA, JT, HL), pp. 4–12.
SIGMODSIGMOD-2014-CaiGLPVJ #algorithm #comparison #implementation #machine learning #scalability
A comparison of platforms for implementing and running very large scale machine learning algorithms (ZC, ZJG, SL, LLP, ZV, CMJ), pp. 1371–1382.
SIGMODSIGMOD-2014-Sedlar #compilation #how
How i learned to stop worrying and love compilers (ES), pp. 1–2.
VLDBVLDB-2014-BoehmTRSTBV #hybrid #machine learning #parallel #scalability
Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML (MB, ST, BR, PS, YT, DB, SV), pp. 553–564.
VLDBVLDB-2014-SunRYD #classification #crowdsourcing #machine learning #named #scalability #using
Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing (CS, NR, FY, AD), pp. 1529–1540.
VLDBVLDB-2014-ZouJLGWX #framework #learning #named
Mariana: Tencent Deep Learning Platform and its Applications (YZ, XJ, YL, ZG, EW, BX), pp. 1772–1777.
VLDBVLDB-2015-MozafariSFJM14 #dataset #learning #scalability
Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning (BM, PS, MJF, MIJ, SM), pp. 125–136.
CSEETCSEET-2014-Ackerman #learning #re-engineering
An active learning module for an introduction to software engineering course (AFA), pp. 190–191.
CSEETCSEET-2014-BoeschS #automation #learning
Automated mentor assignment in blended learning environments (CB, KS), pp. 94–98.
CSEETCSEET-2014-Ding #learning #re-engineering #self
Self-guided learning environment for undergraduate software engineering (JD), pp. 188–189.
CSEETCSEET-2014-FranklBK #development #learning
Learning and working together as prerequisites for the development of high-quality software (GF, SB, BK), pp. 154–157.
CSEETCSEET-2014-KroppMMZ #agile #collaboration #education #learning
Teaching and learning agile collaboration (MK, AM, MM, CGZ), pp. 139–148.
CSEETCSEET-2014-PotterSDW #game studies #learning #named
InspectorX: A game for software inspection training and learning (HP, MS, LD, VW), pp. 55–64.
CSEETCSEET-2014-Wong #challenge #education #experience #lessons learnt #re-engineering
Experience of teaching Executive Master’s program in Software Engineering: Challenges, lessons learned, and path forward (WEW), pp. 186–187.
CSEETCSEET-2014-YamadaIWKFYOKT #development #education #effectiveness #learning
The impacts of personal characteristic on educational effectiveness in controlled-project based learning on software intensive systems development (YY, SI, HW, KK, YF, SY, MO, TK, MT), pp. 119–128.
ITiCSEITiCSE-2014-BainB #programming #question #why
Why is programming so hard to learn? (GB, IB), p. 356.
ITiCSEITiCSE-2014-BerryK #game studies #learning #programming
The state of play: a notional machine for learning programming (MB, MK), pp. 21–26.
ITiCSEITiCSE-2014-EckerdalKTNSM #education #learning
Teaching and learning with MOOCs: computing academics’ perspectives and engagement (AE, PK, NT, AN, JS, LM), pp. 9–14.
ITiCSEITiCSE-2014-EllisH #learning #open source #re-engineering
Structuring software engineering learning within open source software participation (HJCE, GWH), p. 326.
ITiCSEITiCSE-2014-EllisJBPHD #learning
Learning within a professional environment: shared ownership of an HFOSS project (HJCE, SJ, DB, LP, GWH, JD), p. 337.
ITiCSEITiCSE-2014-FalknerVF #identification #learning #self
Identifying computer science self-regulated learning strategies (KF, RV, NJGF), pp. 291–296.
ITiCSEITiCSE-2014-GroverCP #learning
Assessing computational learning in K-12 (SG, SC, RP), pp. 57–62.
ITiCSEITiCSE-2014-Hidalgo-CespedesRL #concept #design #game studies #learning #programming #video
Playing with metaphors: a methodology to design video games for learning abstract programming concepts (JHC, GMR, VLV), p. 348.
ITiCSEITiCSE-2014-Hijon-NeiraVPC #experience #game studies #learning #programming
Game programming for improving learning experience (RBHN, JÁVI, CPR, LC), pp. 225–230.
ITiCSEITiCSE-2014-Jasute #education #geometry #interactive #learning #visualisation
An interactive visualization method of constructionist teaching and learning of geometry (EJ), p. 349.
ITiCSEITiCSE-2014-KothiyalMI #learning #question #scalability
Think-pair-share in a large CS1 class: does learning really happen? (AK, SM, SI), pp. 51–56.
ITiCSEITiCSE-2014-Marcos-Abed #case study #effectiveness #learning #programming
Learning computer programming: a study of the effectiveness of a COAC# (JMA), p. 333.
ITiCSEITiCSE-2014-MedinaSGG #learning #student #using
Learning outcomes using objectives with computer science students (JAM, JJS, EGL, AGC), p. 339.
ITiCSEITiCSE-2014-PirkerRG #education #learning #student
Motivational active learning: engaging university students in computer science education (JP, MRS, CG), pp. 297–302.
ITiCSEITiCSE-2014-PriorCL #case study #experience #learning
Things coming together: learning experiences in a software studio (JP, AC, JL), pp. 129–134.
ITiCSEITiCSE-2014-Rogers #learning #question
New technology, new learning? (YR), p. 1.
ITiCSEITiCSE-2014-TaubBA #learning #physics
The effect of computer science on the learning of computational physics (RT, MBA, MA), p. 352.
ITiCSEITiCSE-2014-Urquiza-FuentesCHMH #framework #learning #social #student #video
A social platform supporting learning through video creation by students (JUF, JC, IH, EM, PAH), p. 330.
ITiCSEITiCSE-2014-Verwaal #learning
Team based learning in theoretical computer science (NV), p. 331.
ITiCSEITiCSE-2014-WartVP #design #learning #problem #social
Apps for social justice: motivating computer science learning with design and real-world problem solving (SVW, SV, TSP), pp. 123–128.
ITiCSEITiCSE-WGR-2014-BrusilovskyEKMB #education #learning
Increasing Adoption of Smart Learning Content for Computer Science Education (PB, SHE, ANK, LM, LB, DB, PI, RP, TS, SAS, JUF, AV, MW), pp. 31–57.
TFPIETFPIE-2014-Walck #haskell #physics #programming
Learn Physics by Programming in Haskell (SNW), pp. 67–77.
TACASTACAS-2014-MalerM #learning #regular expression #scalability
Learning Regular Languages over Large Alphabets (OM, IEM), pp. 485–499.
SANERCSMR-WCRE-2014-XiaFLCW #behaviour #learning #multi #towards
Towards more accurate multi-label software behavior learning (XX, YF, DL, ZC, XW), pp. 134–143.
ICPCICPC-2014-KaulgudAMT #comprehension #learning
Comprehension support during knowledge transitions: learning from field (VSK, KMA, JM, GT), pp. 205–206.
ICSMEICSME-2014-BinkleyL #information retrieval #learning #rank
Learning to Rank Improves IR in SE (DB, DJL), pp. 441–445.
ICSMEICSME-2014-XuanM #fault #learning #locality #metric #multi #ranking
Learning to Combine Multiple Ranking Metrics for Fault Localization (JX, MM), pp. 191–200.
STOCSTOC-2014-AwasthiBL #learning #linear #locality #power of
The power of localization for efficiently learning linear separators with noise (PA, MFB, PML), pp. 449–458.
STOCSTOC-2014-Christiano #learning #online #programming
Online local learning via semidefinite programming (PC), pp. 468–474.
STOCSTOC-2014-DanielyLS #complexity #learning
From average case complexity to improper learning complexity (AD, NL, SSS), pp. 441–448.
ICALPICALP-v1-2014-Volkovich #bound #learning #on the
On Learning, Lower Bounds and (un)Keeping Promises (IV), pp. 1027–1038.
ICALPICALP-v2-2014-DamsHK #learning #network
Jamming-Resistant Learning in Wireless Networks (JD, MH, TK), pp. 447–458.
LATALATA-2014-LaurenceLNST #learning #transducer
Learning Sequential Tree-to-Word Transducers (GL, AL, JN, SS, MT), pp. 490–502.
FMFM-2014-LinH #composition #concurrent #learning #model checking #synthesis
Compositional Synthesis of Concurrent Systems through Causal Model Checking and Learning (SWL, PAH), pp. 416–431.
SEFMSEFM-2014-CasselHJS #finite #learning #state machine
Learning Extended Finite State Machines (SC, FH, BJ, BS), pp. 250–264.
CHICHI-2014-DontchevaMBG #crowdsourcing #learning #performance
Combining crowdsourcing and learning to improve engagement and performance (MD, RRM, JRB, EMG), pp. 3379–3388.
CHICHI-2014-DunwellFPHALS #approach #game studies #learning #safety
A game-based learning approach to road safety: the code of everand (ID, SdF, PP, MH, SA, PL, CDS), pp. 3389–3398.
CHICHI-2014-GreenbergG #learning #online
Learning to fail: experiencing public failure online through crowdfunding (MDG, EG), pp. 581–590.
CHICHI-2014-KovacsM #learning
Smart subtitles for vocabulary learning (GK, RCM), pp. 853–862.
CHICHI-2014-KuleszaACFC #concept #evolution #machine learning
Structured labeling for facilitating concept evolution in machine learning (TK, SA, RC, DF, DXC), pp. 3075–3084.
CHICHI-2014-MentisCS #learning
Learning to see the body: supporting instructional practices in laparoscopic surgical procedures (HMM, AC, SDS), pp. 2113–2122.
CHICHI-2014-MonserratLZC #interactive #learning
L.IVE: an integrated interactive video-based learning environment (TJKPM, YL, SZ, XC), pp. 3399–3402.
CHICHI-2014-PilliasRL #design #game studies #lessons learnt #video
Designing tangible video games: lessons learned from the sifteo cubes (CP, RRB, GL), pp. 3163–3166.
CHICHI-2014-Ruggiero #game studies #learning #named #persuasion #student #towards #video
Spent: changing students’ affective learning toward homelessness through persuasive video game play (DNR), pp. 3423–3432.
CSCWCSCW-2014-MillerZGG #collaboration #learning #people #research
Pair research: matching people for collaboration, learning, and productivity (RCM, HZ, EG, EG), pp. 1043–1048.
CSCWCSCW-2014-YuAKK #comparison #learning #quality #social
A comparison of social, learning, and financial strategies on crowd engagement and output quality (LY, PA, AK, RK), pp. 967–978.
CSCWCSCW-2014-ZhuDKK #assessment #learning #performance
Reviewing versus doing: learning and performance in crowd assessment (HZ, SPD, REK, AK), pp. 1445–1455.
HCIDHM-2014-GotoYTWS
Application of E-learning System Reality in Kyoto-style Earthen Wall Training (AG, HY, YT, ZW, HS), pp. 247–253.
HCIDUXU-DI-2014-ChangH
Effect of Perception-Compatibility, Learning-Factor, and Symbol-Carrier on Single LED Symbol System Recognizing (CCC, TKPH), pp. 417–424.
HCIDUXU-DI-2014-GencerBZV #detection #machine learning #mobile
Detection of Churned and Retained Users with Machine Learning Methods for Mobile Applications (MG, GB, ÖZ, TV), pp. 234–245.
HCIDUXU-DI-2014-ShafiqICRAAR #analysis #case study #learning #smarttech #usability #user satisfaction #what
To What Extent System Usability Effects User Satisfaction: A Case Study of Smart Phone Features Analysis for Learning of Novice (MS, MI, JGC, ZR, MA, WA, SR), pp. 346–357.
HCIDUXU-DI-2014-Souto #design #experience #interactive #learning #user interface #visualisation
Interactive Visualizations in Learning Mathematics: Implications for Information Design and User Experience (VTS), pp. 472–480.
HCIDUXU-ELAS-2014-KarlinPC #experience #learning #online #user interface
Pumping Up the Citizen Muscle Bootcamp: Improving User Experience in Online Learning (BK, BP, AC), pp. 562–573.
HCIDUXU-ELAS-2014-Martins #industrial #learning #prototype
Prototyping in a Learning Environment — Digital Publishing Projects from the Escola Superior de Desenho Industrial (MAFM), pp. 195–206.
HCIDUXU-ELAS-2014-MedeirosJG #learning #memory management #named #student
Logograms: Memory Aids for Learning, and an Example with Hearing-Impaired Students (LM, MBJ, LVG), pp. 207–216.
HCIDUXU-ELAS-2014-MustafaMMAAMEBK #development #interface #learning #multi
Rural Area Development through Multi-interface Technology and Virtual Learning System (FuM, AM, SM, SA, UA, SM, HE, TAB, MFK), pp. 442–451.
HCIDUXU-ELAS-2014-Portugal #design
Design, User-Experience and Teaching-Learning (CP), pp. 230–241.
HCIDUXU-TMT-2014-BrangierD #case study #heuristic #persuasion
Heuristic Inspection to Assess Persuasiveness: A Case Study of a Mathematics E-learning Program (EB, MCD), pp. 425–436.
HCIHCI-AIMT-2014-AlkhashramiAA #design #interface #learning
Human Factors in the Design of Arabic-Language Interfaces in Assistive Technologies for Learning Difficulties (SA, HA, AAW), pp. 362–369.
HCIHCI-AIMT-2014-MikamiM #3d #effectiveness #learning
Effectiveness of Virtual Hands in 3D Learning Material (TM, SM), pp. 93–101.
HCIHCI-AIMT-2014-YanikTMMBGW #gesture #learning
A Method for Lifelong Gesture Learning Based on Growing Neural Gas (PMY, AT, JM, JM, JOB, KEG, IDW), pp. 191–202.
HCIHCI-AS-2014-DiasDH #fuzzy #interactive #modelling #quality #using
Exploring B-Learning Scenarios Using Fuzzy Logic-Based Modeling of Users’ LMS Quality of Interaction in Ergonomics and Psychomotor Rehabilitation Academic Courses (SBD, JAD, LJH), pp. 233–243.
HCIHCI-AS-2014-JanssonSBAT #automation #design
Authority and Level of Automation — Lessons to Be Learned in Design of In-vehicle Assistance Systems (AJ, PS, IB, AA, ST), pp. 413–424.
HCIHCI-AS-2014-SchwallerKAL #feedback #gesture #learning #visual notation
Improving In-game Gesture Learning with Visual Feedback (MS, JK, LA, DL), pp. 643–653.
HCIHCI-TMT-2014-MatsumotoKKA #adaptation #automation #learning #student #word
Evaluating an Automatic Adaptive Delivery Method of English Words Learning Contents for University Students in Science and Technology (SM, TK, TK, MA), pp. 510–520.
HCIHCI-TMT-2014-MorDHF #education #human-computer #learning #online
Teaching and Learning HCI Online (EM, MGD, EH, NF), pp. 230–241.
HCIHCI-TMT-2014-SilvaCP #education #human-computer #interactive #learning
Studio-Based Learning as a Natural Fit to Teaching Human-Computer Interaction (PAS, MEC, BJP), pp. 251–258.
HCIHCI-TMT-2014-YajimaTS #collaboration #learning
Proposal of Collaborative Learning Support Method in Risk Communications (HY, NT, RS), pp. 457–465.
HCIHIMI-AS-2014-AraiKTKA #comprehension #development #learning #source code
Development of a Learning Support System for Source Code Reading Comprehension (TA, HK, TT, YK, TA), pp. 12–19.
HCIHIMI-AS-2014-HirashimaYH #learning #problem #word
Triplet Structure Model of Arithmetical Word Problems for Learning by Problem-Posing (TH, SY, YH), pp. 42–50.
HCIHIMI-AS-2014-HirokawaFSY #learning #mindmap
Learning Winespeak from Mind Map of Wine Blogs (SH, BF, TS, CY), pp. 383–393.
HCIHIMI-AS-2014-MatsuiHKA #behaviour #case study #education #learning
A Study on Exploration of Relationships between Behaviors and Mental States of Learners for Value Co-creative Education and Learning Environment (TM, YH, KK, TA), pp. 69–79.
HCIHIMI-AS-2014-MikamiT #learning #music #performance
A Music Search System for Expressive Music Performance Learning (TM, KT), pp. 80–89.
HCIHIMI-AS-2014-TogawaK #collaboration #framework #smarttech #using
Private Cloud Collaboration Framework for e-Learning Environment for Disaster Recovery Using Smartphone Alert Notification (ST, KK), pp. 118–126.
HCIHIMI-AS-2014-UeiFKNKS #design #education #evaluation #learning
Learning Effect Evaluation of an Educational Tool for Product-Service System Design Based on Learner Viewpoints (KU, TF, AK, YN, KK, YS), pp. 643–652.
HCIHIMI-AS-2014-YamaguchiTT #learning #process #visualisation
Visualizing Mental Learning Processes with Invisible Mazes for Continuous Learning (TY, KT, KT), pp. 137–148.
HCIHIMI-DE-2014-LinKT #analysis #collaboration #design #learning
A Learning Method for Product Analysis in Product Design — Learning Method of Product Analysis Utilizing Collaborative Learning and a List of Analysis Items (HL, HK, TT), pp. 503–513.
HCILCT-NLE-2014-Choffat-Durr #distance #process
Distance Exchange Projects at Elementary School: A Focus on a Co-learning Process (ACD), pp. 380–387.
HCILCT-NLE-2014-KaprosP #learning
Empowering L&D Managers through Customisation of Inline Learning Analytics (EK, NP), pp. 282–291.
HCILCT-NLE-2014-Kim #feedback #learning #self #simulation
Simulation Training in Self-Regulated Learning: Investigating the Effects of Dual Feedback on Dynamic Decision-Making Tasks (JHK), pp. 419–428.
HCILCT-NLE-2014-LimongelliS #fuzzy #modelling #personalisation #student
Fuzzy Student Modeling for Personalization of e-Learning Courses (CL, FS), pp. 292–301.
HCILCT-NLE-2014-Milde #editing #html #learning #online
An HTML5-Based Online Editor for Creating Annotated Learning Videos (JTM), pp. 172–179.
HCILCT-NLE-2014-MirandaIC #framework #information management
From Information Systems to e-Learning 3.0 Systems’s Critical Success Factors: A Framework Proposal (PM, PTI, CJC), pp. 180–191.
HCILCT-NLE-2014-MoissaCG #adaptation #behaviour #student #visualisation #web
A Web Analytics and Visualization Tool to Understand Students’ Behavior in an Adaptive E-Learning System (BM, LSdC, IG), pp. 312–321.
HCILCT-NLE-2014-MorGHH #assessment #design #learning #tool support
Designing Learning Tools: The Case of a Competence Assessment Tool (EM, AEGR, EH, MAH), pp. 83–94.
HCILCT-NLE-2014-MoriT #development #learning
Development of a Fieldwork Support System for Group Work in Project-Based Learning (MM, AT), pp. 429–440.
HCILCT-NLE-2014-Piki #collaboration #learning #process #question
Learner Engagement in Computer-Supported Collaborative Learning Activities: Natural or Nurtured? (AP), pp. 107–118.
HCILCT-NLE-2014-Said #sorting
Card Sorting Assessing User Attitude in E-Learning (GRES), pp. 261–272.
HCILCT-NLE-2014-TaraghiSES #classification #learning #markov #multi
Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication (BT, AS, ME, MS), pp. 322–333.
HCILCT-NLE-2014-UlbrichtBFQ #component #interface #learning #testing #usability
The Emotion Component on Usability Testing Human Computer Interface of an Inclusive Learning Management System (VRU, CHB, LF, SRPdQ), pp. 334–345.
HCILCT-NLE-2014-UzunosmanogluC #collaboration #learning #online #paradigm
Examining an Online Collaboration Learning Environment with the Dual Eye-Tracking Paradigm: The Case of Virtual Math Teams (SDU, MPÇ), pp. 462–472.
HCILCT-NLE-2014-VasiliouIZ #case study #experience #learning #multimodal #student
Measuring Students’ Flow Experience in a Multimodal Learning Environment: A Case Study (CV, AI, PZ), pp. 346–357.
HCILCT-NLE-2014-WangLC #learning #online #student
Low-Achieving Students’ Perceptions of Online Language Learning: A Case of English Proficiency Threshold (ALW, YCL, SFC), pp. 250–258.
HCILCT-TRE-2014-Bharali #learning #online #process
Enhancing Online Learning Activities for Groups in Flipped Classrooms (RB), pp. 269–276.
HCILCT-TRE-2014-BraunhoferEGR #learning #mobile #recommendation
Context Dependent Preference Acquisition with Personality-Based Active Learning in Mobile Recommender Systems (MB, ME, MG, FR), pp. 105–116.
HCILCT-TRE-2014-Castro #case study #collaboration #learning #named
Mosca — A Case Study on Collaborative Work — Combining Dimensions while Learning (SC), pp. 388–396.
HCILCT-TRE-2014-EradzeL #design #interactive #learning
Interrelation between Pedagogical Design and Learning Interaction Patterns in different Virtual Learning Environments (ME, ML), pp. 23–32.
HCILCT-TRE-2014-Hayes14a #approach #development #game studies #learning #simulation
An Approach to Holistic Development of Serious Games and Learning Simulations (ATH), pp. 42–49.
HCILCT-TRE-2014-HiramatsuIFS #development #learning #using
Development of the Learning System for Outdoor Study Using Zeigarnik Effect (YH, AI, MF, FS), pp. 127–137.
HCILCT-TRE-2014-IkedaS #learning
Dream Drill: A Bedtime Learning Application (AI, IS), pp. 138–145.
HCILCT-TRE-2014-IshikawaAKSTD #learning #process #self #student
Sustaining Outside-of-Class CALL Activities by Means of a Student Self-Evaluation System in a University Blended Learning EFL Course (YI, RAY, MK, CS, YT, MD), pp. 146–154.
HCILCT-TRE-2014-MartinezMLLC #3d #interactive #learning
Supporting Learning with 3D Interactive Applications in Early Years (ACM, MJMS, MLS, DCPL, MC), pp. 11–22.
HCILCT-TRE-2014-MartinWH #interactive #learning #mobile
Sensor Based Interaction Mechanisms in Mobile Learning (KUM, MW, WH), pp. 165–172.
HCILCT-TRE-2014-OliveiraM #learning #network #research
Digital Identity of Researchers and Their Personal Learning Network (NRO, LM), pp. 467–477.
HCILCT-TRE-2014-ShahoumianSZPH #education #learning #simulation
Blended Simulation Based Medical Education: A Complex Learning/Training Opportunity (AS, MS, MZ, GP, JH), pp. 478–485.
HCILCT-TRE-2014-ShimizuO #effectiveness #learning #question
Which Is More Effective for Learning German and Japanese Language, Paper or Digital? (RS, KO), pp. 309–318.
HCILCT-TRE-2014-SzklannyW #learning #prototype
Prototyping M-Learning Course on the Basis of Puzzle Learning Methodology (KS, MW), pp. 215–226.
HCILCT-TRE-2014-YamaguchiSYNSM #collaboration #detection #distance #learning
Posture and Face Detection with Dynamic Thumbnail Views for Collaborative Distance Learning (TY, HS, MY, YN, HS, TM), pp. 227–236.
AdaEuropeAdaEurope-2014-Laine #lessons learnt
Lessons Learned and Easily Forgotten (RL), pp. 1–6.
HILTHILT-2014-BarnesT #ada #design #lessons learnt
Ada 83 to Ada 2012: lessons learned over 30 years of language design (JB, STT), pp. 3–4.
ICEISICEIS-v1-2014-ShakirIB #machine learning #topic
Machine Learning Techniques for Topic Spotting (NS, EI, ISB), pp. 450–455.
ICEISICEIS-v2-2014-MahmoudBAG #approach #learning
A New Approach Based on Learning Services to Generate Appropriate Learning Paths (CBM, FB, MHA, FG), pp. 643–646.
ICEISICEIS-v2-2014-OtonBGGB #learning #metadata #using
Description of Accessible Learning Resources by Using Metadata (SO, CB, EG, AGC, RB), pp. 620–626.
ICEISICEIS-v2-2014-ZhengJL #hybrid #learning #taxonomy #using
Cross-Sensor Iris Matching using Patch-based Hybrid Dictionary Learning (BRZ, DYJ, YHL), pp. 169–174.
ICEISICEIS-v3-2014-AzevedoF #case study #education #learning #process #student
The Response Systems in the Student’s Learning/Teaching Process — A Case Study in a Portuguese School (PA, MJF), pp. 79–86.
ICEISICEIS-v3-2014-BalinaAMS #development #metamodelling
Meta Model of e-Learning Materials Development (SB, IA, IM, ES), pp. 150–155.
ICEISICEIS-v3-2014-PaulinsBA #visualisation
e-Learning Material Presentation and Visualization Types and Schemes (NP, SB, IA), pp. 138–143.
CIKMCIKM-2014-DeBBGC #learning #linear
Learning a Linear Influence Model from Transient Opinion Dynamics (AD, SB, PB, NG, SC), pp. 401–410.
CIKMCIKM-2014-DeveaudAMO #learning #on the #rank
On the Importance of Venue-Dependent Features for Learning to Rank Contextual Suggestions (RD, MDA, CM, IO), pp. 1827–1830.
CIKMCIKM-2014-GoncalvesDCSZB #learning #multi
Multi-task Sparse Structure Learning (ARG, PD, SC, VS, FJVZ, AB), pp. 451–460.
CIKMCIKM-2014-JinZXDLH #learning #multi
Multi-task Multi-view Learning for Heterogeneous Tasks (XJ, FZ, HX, CD, PL, QH), pp. 441–450.
CIKMCIKM-2014-MaoWHO #classification #learning #linear #multi
Nonlinear Classification via Linear SVMs and Multi-Task Learning (XM, OW, WH, PO), pp. 1955–1958.
CIKMCIKM-2014-PfeifferNB #learning #network #probability #using
Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference (JJPI, JN, PNB), pp. 639–648.
CIKMCIKM-2014-PimplikarGBP #learning
Learning to Propagate Rare Labels (RP, DG, DB, GRP), pp. 201–210.
CIKMCIKM-2014-ShiKBLH #learning #named #recommendation
CARS2: Learning Context-aware Representations for Context-aware Recommendations (YS, AK, LB, ML, AH), pp. 291–300.
CIKMCIKM-2014-VinzamuriLR #learning
Active Learning based Survival Regression for Censored Data (BV, YL, CKR), pp. 241–250.
CIKMCIKM-2014-WangMC #learning #parametricity
Structure Learning via Parameter Learning (WYW, KM, WWC), pp. 1199–1208.
CIKMCIKM-2014-WuHPZCZ #feature model #learning #multi
Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning (JW, ZH, SP, XZ, ZC, CZ), pp. 1699–1708.
CIKMCIKM-2014-XiePLW #framework #image #learning #multi
A Cross-modal Multi-task Learning Framework for Image Annotation (LX, PP, YL, SW), pp. 431–440.
CIKMCIKM-2014-YangTZ #learning #streaming
Active Learning for Streaming Networked Data (ZY, JT, YZ), pp. 1129–1138.
CIKMCIKM-2014-YaoRSLF #locality #probability
Exploring Tag-Free RFID-Based Passive Localization and Tracking via Learning-Based Probabilistic Approaches (LY, WR, QZS, XL, NJGF), pp. 1799–1802.
CIKMCIKM-2014-YuX #interactive #learning #network #predict #scalability #social
Learning Interactions for Social Prediction in Large-scale Networks (XY, JX), pp. 161–170.
CIKMCIKM-2014-ZhongPXYM #adaptation #collaboration #learning #recommendation
Adaptive Pairwise Preference Learning for Collaborative Recommendation with Implicit Feedbacks (HZ, WP, CX, ZY, ZM), pp. 1999–2002.
CIKMCIKM-2014-ZhuSY #information retrieval #learning #taxonomy
Cross-Modality Submodular Dictionary Learning for Information Retrieval (FZ, LS, MY), pp. 1479–1488.
ECIRECIR-2014-BauerCRG #corpus #formal method #learning #web
Learning a Theory of Marriage (and Other Relations) from a Web Corpus (SB, SC, LR, TG), pp. 591–597.
ECIRECIR-2014-BreussT #interactive #learning #recommendation #social #social media
Learning from User Interactions for Recommending Content in Social Media (MB, MT), pp. 598–604.
ECIRECIR-2014-FiliceCCB #effectiveness #kernel #learning #online
Effective Kernelized Online Learning in Language Processing Tasks (SF, GC, DC, RB), pp. 347–358.
ECIRECIR-2014-NainiA #feature model #learning #rank
Exploiting Result Diversification Methods for Feature Selection in Learning to Rank (KDN, ISA), pp. 455–461.
ECIRECIR-2014-QiDCW #information management #learning
Deep Learning for Character-Based Information Extraction (YQ, SGD, RC, JW), pp. 668–674.
ICMLICML-c1-2014-AroraBGM #bound #learning
Provable Bounds for Learning Some Deep Representations (SA, AB, RG, TM), pp. 584–592.
ICMLICML-c1-2014-DenisGH #bound #learning #matrix
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning (FD, MG, AH), pp. 449–457.
ICMLICML-c1-2014-DickGS #learning #markov #online #process #sequence
Online Learning in Markov Decision Processes with Changing Cost Sequences (TD, AG, CS), pp. 512–520.
ICMLICML-c1-2014-JainT #bound #independence #learning
(Near) Dimension Independent Risk Bounds for Differentially Private Learning (PJ, AGT), pp. 476–484.
ICMLICML-c1-2014-LacosteMLL #learning
Agnostic Bayesian Learning of Ensembles (AL, MM, FL, HL), pp. 611–619.
ICMLICML-c1-2014-LajugieBA #clustering #learning #metric #problem
Large-Margin Metric Learning for Constrained Partitioning Problems (RL, FRB, SA), pp. 297–305.
ICMLICML-c1-2014-LuoS #learning #online #towards
Towards Minimax Online Learning with Unknown Time Horizon (HL, RES), pp. 226–234.
ICMLICML-c1-2014-MohriM #algorithm #learning #optimisation
Learning Theory and Algorithms for revenue optimization in second price auctions with reserve (MM, AMM), pp. 262–270.
ICMLICML-c1-2014-RooshenasL #interactive #learning #network
Learning Sum-Product Networks with Direct and Indirect Variable Interactions (AR, DL), pp. 710–718.
ICMLICML-c1-2014-ShalitC #coordination #learning #matrix #orthogonal
Coordinate-descent for learning orthogonal matrices through Givens rotations (US, GC), pp. 548–556.
ICMLICML-c1-2014-ShiZ #learning #online
Online Bayesian Passive-Aggressive Learning (TS, JZ), pp. 378–386.
ICMLICML-c1-2014-SolomonRGB #learning
Wasserstein Propagation for Semi-Supervised Learning (JS, RMR, LJG, AB), pp. 306–314.
ICMLICML-c1-2014-TandonR #graph #learning
Learning Graphs with a Few Hubs (RT, PDR), pp. 602–610.
ICMLICML-c1-2014-Yu0KD #learning #multi #scalability
Large-scale Multi-label Learning with Missing Labels (HFY, PJ, PK, ISD), pp. 593–601.
ICMLICML-c2-2014-AffandiFAT #kernel #learning #parametricity #process
Learning the Parameters of Determinantal Point Process Kernels (RHA, EBF, RPA, BT), pp. 1224–1232.
ICMLICML-c2-2014-AminHK #learning
Learning from Contagion (Without Timestamps) (KA, HH, MK), pp. 1845–1853.
ICMLICML-c2-2014-AndoniPV0 #learning #network
Learning Polynomials with Neural Networks (AA, RP, GV, LZ), pp. 1908–1916.
ICMLICML-c2-2014-AziziAG #composition #learning #network
Learning Modular Structures from Network Data and Node Variables (EA, EA, JEG), pp. 1440–1448.
ICMLICML-c2-2014-BalleHP #comparison #empirical #learning #probability
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison (BB, WLH, JP), pp. 1386–1394.
ICMLICML-c2-2014-Bou-AmmarERT #learning #multi #online #policy
Online Multi-Task Learning for Policy Gradient Methods (HBA, EE, PR, MET), pp. 1206–1214.
ICMLICML-c2-2014-BrunskillL #learning
PAC-inspired Option Discovery in Lifelong Reinforcement Learning (EB, LL), pp. 316–324.
ICMLICML-c2-2014-Chen0 #big data #learning #modelling #topic #using
Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data (ZC, BL), pp. 703–711.
ICMLICML-c2-2014-CohenW #commutative #learning
Learning the Irreducible Representations of Commutative Lie Groups (TC, MW), pp. 1755–1763.
ICMLICML-c2-2014-DuLBS #information management #learning #network
Influence Function Learning in Information Diffusion Networks (ND, YL, MFB, LS), pp. 2016–2024.
ICMLICML-c2-2014-FangCL #graph #learning
Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically (YF, KCCC, HWL), pp. 406–414.
ICMLICML-c2-2014-GrandeWH #learning #performance #process
Sample Efficient Reinforcement Learning with Gaussian Processes (RCG, TJW, JPH), pp. 1332–1340.
ICMLICML-c2-2014-HoangLJK #learning #process
Nonmyopic ϵ-Bayes-Optimal Active Learning of Gaussian Processes (TNH, BKHL, PJ, MSK), pp. 739–747.
ICMLICML-c2-2014-HoulsbyHG #learning #matrix #robust
Cold-start Active Learning with Robust Ordinal Matrix Factorization (NH, JMHL, ZG), pp. 766–774.
ICMLICML-c2-2014-HuS #machine learning #multi #predict
Multi-period Trading Prediction Markets with Connections to Machine Learning (JH, AJS), pp. 1773–1781.
ICMLICML-c2-2014-JawanpuriaVN #feature model #kernel #learning #multi #on the
On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection (PJ, MV, JSN), pp. 118–126.
ICMLICML-c2-2014-KricheneDB #convergence #learning #on the
On the convergence of no-regret learning in selfish routing (WK, BD, AMB), pp. 163–171.
ICMLICML-c2-2014-LevineK #learning #network #optimisation #policy
Learning Complex Neural Network Policies with Trajectory Optimization (SL, VK), pp. 829–837.
ICMLICML-c2-2014-LiG #classification #learning #representation #semantics
Latent Semantic Representation Learning for Scene Classification (XL, YG), pp. 532–540.
ICMLICML-c2-2014-LimL #learning #metric #performance #ranking
Efficient Learning of Mahalanobis Metrics for Ranking (DL, GRGL), pp. 1980–1988.
ICMLICML-c2-2014-LinK #constraints #learning #performance #representation
Stable and Efficient Representation Learning with Nonnegativity Constraints (THL, HTK), pp. 1323–1331.
ICMLICML-c2-2014-LinYHY #distance #learning
Geodesic Distance Function Learning via Heat Flow on Vector Fields (BL, JY, XH, JY), pp. 145–153.
ICMLICML-c2-2014-LiuD #learning #problem #set
Learnability of the Superset Label Learning Problem (LPL, TGD), pp. 1629–1637.
ICMLICML-c2-2014-LiZ #higher-order #learning #problem
High Order Regularization for Semi-Supervised Learning of Structured Output Problems (YL, RSZ), pp. 1368–1376.
ICMLICML-c2-2014-LiZ0 #learning #multi
Bayesian Max-margin Multi-Task Learning with Data Augmentation (CL, JZ, JC), pp. 415–423.
ICMLICML-c2-2014-MengEH #learning #modelling #visual notation
Learning Latent Variable Gaussian Graphical Models (ZM, BE, AOHI), pp. 1269–1277.
ICMLICML-c2-2014-MizrahiDF #learning #linear #markov #parallel #random
Linear and Parallel Learning of Markov Random Fields (YDM, MD, NdF), pp. 199–207.
ICMLICML-c2-2014-MnihG #learning #network
Neural Variational Inference and Learning in Belief Networks (AM, KG), pp. 1791–1799.
ICMLICML-c2-2014-NiuDPS #approximate #learning #multi
Transductive Learning with Multi-class Volume Approximation (GN, BD, MCdP, MS), pp. 1377–1385.
ICMLICML-c2-2014-PandeyD #learning #network
Learning by Stretching Deep Networks (GP, AD), pp. 1719–1727.
ICMLICML-c2-2014-PentinaL #bound #learning
A PAC-Bayesian bound for Lifelong Learning (AP, CHL), pp. 991–999.
ICMLICML-c2-2014-QinLJ #learning #optimisation
Sparse Reinforcement Learning via Convex Optimization (ZQ, WL, FJ), pp. 424–432.
ICMLICML-c2-2014-ReedSZL #interactive #learning
Learning to Disentangle Factors of Variation with Manifold Interaction (SR, KS, YZ, HL), pp. 1431–1439.
ICMLICML-c2-2014-RippelGA #learning #order
Learning Ordered Representations with Nested Dropout (OR, MAG, RPA), pp. 1746–1754.
ICMLICML-c2-2014-RodriguesPR #classification #learning #multi #process
Gaussian Process Classification and Active Learning with Multiple Annotators (FR, FCP, BR), pp. 433–441.
ICMLICML-c2-2014-SantosZ #learning
Learning Character-level Representations for Part-of-Speech Tagging (CNdS, BZ), pp. 1818–1826.
ICMLICML-c2-2014-SilvaKB #learning
Active Learning of Parameterized Skills (BCdS, GK, AGB), pp. 1737–1745.
ICMLICML-c2-2014-SongGJMHD #learning #locality #on the
On learning to localize objects with minimal supervision (HOS, RBG, SJ, JM, ZH, TD), pp. 1611–1619.
ICMLICML-c2-2014-SunIM #classification #learning #linear
Learning Mixtures of Linear Classifiers (YS, SI, AM), pp. 721–729.
ICMLICML-c2-2014-SunM #geometry #learning #statistics
An Information Geometry of Statistical Manifold Learning (KS, SMM), pp. 1–9.
ICMLICML-c2-2014-TrigeorgisBZS #learning
A Deep Semi-NMF Model for Learning Hidden Representations (GT, KB, SZ, BWS), pp. 1692–1700.
ICMLICML-c2-2014-WangHS #learning
Active Transfer Learning under Model Shift (XW, TKH, JS), pp. 1305–1313.
ICMLICML-c2-2014-WangNH #distance #learning #metric #robust
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization (HW, FN, HH), pp. 1836–1844.
ICMLICML-c2-2014-WangSSMK #learning #metric
Two-Stage Metric Learning (JW, KS, FS, SMM, AK), pp. 370–378.
ICMLICML-c2-2014-WenYG #learning #nondeterminism #robust
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification (JW, CNY, RG), pp. 631–639.
ICMLICML-c2-2014-WuCLY #behaviour #consistency #learning #network #predict #social
Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks (SHW, HHC, KHL, PSY), pp. 298–306.
ICPRICPR-2014-AkinM #detection #learning #online
Online Learning and Detection with Part-Based, Circulant Structure (OA, KM), pp. 4229–4233.
ICPRICPR-2014-Al-HalahRS #learning #metric #semantics #similarity #what
What to Transfer? High-Level Semantics in Transfer Metric Learning for Action Similarity (ZAH, LR, RS), pp. 2775–2780.
ICPRICPR-2014-Alvarez-MezaMC #adaptation #learning #video
Correntropy-Based Adaptive Learning to Support Video Surveillance Systems (AMÁM, SMG, GCD), pp. 2590–2595.
ICPRICPR-2014-AodhaSBTGJ #interactive #machine learning
Putting the Scientist in the Loop — Accelerating Scientific Progress with Interactive Machine Learning (OMA, VS, GJB, MT, MAG, KEJ), pp. 9–17.
ICPRICPR-2014-ArvanitopoulosBT #analysis #learning
Laplacian Support Vector Analysis for Subspace Discriminative Learning (NA, DB, AT), pp. 1609–1614.
ICPRICPR-2014-BargiXP #adaptation #classification #infinity #learning #online #segmentation #streaming
An Infinite Adaptive Online Learning Model for Segmentation and Classification of Streaming Data (AB, RYDX, MP), pp. 3440–3445.
ICPRICPR-2014-BayramogluKEANKH #approach #detection #image #machine learning #using
Detection of Tumor Cell Spheroids from Co-cultures Using Phase Contrast Images and Machine Learning Approach (NB, MK, LE, MA, MN, JK, JH), pp. 3345–3350.
ICPRICPR-2014-BertonL #graph #learning
Graph Construction Based on Labeled Instances for Semi-supervised Learning (LB, AdAL), pp. 2477–2482.
ICPRICPR-2014-BouillonA #classification #evolution #gesture #learning #online
Supervision Strategies for the Online Learning of an Evolving Classifier for Gesture Commands (MB, ÉA), pp. 2029–2034.
ICPRICPR-2014-CaiTF #learning #recognition #taxonomy
Learning Pose Dictionary for Human Action Recognition (JxC, XT, GCF), pp. 381–386.
ICPRICPR-2014-CaoHS #approach #classification #kernel #learning #multi
Optimization-Based Extreme Learning Machine with Multi-kernel Learning Approach for Classification (LlC, WbH, FS), pp. 3564–3569.
ICPRICPR-2014-ChengZHT #learning #recognition
Semi-supervised Learning for RGB-D Object Recognition (YC, XZ, KH, TT), pp. 2377–2382.
ICPRICPR-2014-ChenK14a #learning
Learning to Count with Back-propagated Information (KC, JKK), pp. 4672–4677.
ICPRICPR-2014-ChenZW #identification #learning #metric
Relevance Metric Learning for Person Re-identification by Exploiting Global Similarities (JC, ZZ, YW), pp. 1657–1662.
ICPRICPR-2014-CheplyginaSTPLB #classification #learning #multi
Classification of COPD with Multiple Instance Learning (VC, LS, DMJT, JJHP, ML, MdB), pp. 1508–1513.
ICPRICPR-2014-CruzSC #on the
On Meta-learning for Dynamic Ensemble Selection (RMOC, RS, GDCC), pp. 1230–1235.
ICPRICPR-2014-DengZS #learning #recognition #speech
Linked Source and Target Domain Subspace Feature Transfer Learning — Exemplified by Speech Emotion Recognition (JD, ZZ, BWS), pp. 761–766.
ICPRICPR-2014-DuZCW #flexibility #learning #linear #random
Learning Flexible Binary Code for Linear Projection Based Hashing with Random Forest (SD, WZ, SC, YW), pp. 2685–2690.
ICPRICPR-2014-FangZ #classification #learning
Cross Domain Shared Subspace Learning for Unsupervised Transfer Classification (ZF, ZZ), pp. 3927–3932.
ICPRICPR-2014-FanSCD #framework #learning #online #robust #taxonomy
A Unified Online Dictionary Learning Framework with Label Information for Robust Object Tracking (BF, JS, YC, YD), pp. 2311–2316.
ICPRICPR-2014-FiratCV #detection #learning #representation
Representation Learning for Contextual Object and Region Detection in Remote Sensing (OF, GC, FTYV), pp. 3708–3713.
ICPRICPR-2014-FornoniC #learning #naive bayes #recognition
Scene Recognition with Naive Bayes Non-linear Learning (MF, BC), pp. 3404–3409.
ICPRICPR-2014-GanSZ #learning
An Extended Isomap for Manifold Topology Learning with SOINN Landmarks (QG, FS, JZ), pp. 1579–1584.
ICPRICPR-2014-GeDGC #learning
Background Subtraction with Dynamic Noise Sampling and Complementary Learning (WG, YD, ZG, YC), pp. 2341–2346.
ICPRICPR-2014-GengWX #adaptation #estimation #learning
Facial Age Estimation by Adaptive Label Distribution Learning (XG, QW, YX), pp. 4465–4470.
ICPRICPR-2014-GienTCL #fuzzy #learning #multi #predict
Dual Fuzzy Hypergraph Regularized Multi-label Learning for Protein Subcellular Location Prediction (JG, YYT, CLPC, YL), pp. 512–516.
ICPRICPR-2014-GuoZLCZ #clustering #kernel #learning #multi
Multiple Kernel Learning Based Multi-view Spectral Clustering (DG, JZ, XL, YC, CZ), pp. 3774–3779.
ICPRICPR-2014-HooKPC #comprehension #image #learning #random
Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding (WLH, TKK, YP, CSC), pp. 3434–3439.
ICPRICPR-2014-HouYW #adaptation #learning #recognition #self
Domain Adaptive Self-Taught Learning for Heterogeneous Face Recognition (CAH, MCY, YCFW), pp. 3068–3073.
ICPRICPR-2014-HuDG #experience #learning #online #recognition #visual notation
Online Regression of Grandmother-Cell Responses with Visual Experience Learning for Face Recognition (JH, WD, JG), pp. 4606–4611.
ICPRICPR-2014-JhuoL #detection #learning #multi #video
Video Event Detection via Multi-modality Deep Learning (IHJ, DTL), pp. 666–671.
ICPRICPR-2014-KhoshrouCT #learning #multi #video
Active Learning from Video Streams in a Multi-camera Scenario (SK, JSC, LFT), pp. 1248–1253.
ICPRICPR-2014-KrauseGDLF #fine-grained #learning #recognition
Learning Features and Parts for Fine-Grained Recognition (JK, TG, JD, LJL, FFL), pp. 26–33.
ICPRICPR-2014-KumarG #documentation #keyword #learning
Bayesian Active Learning for Keyword Spotting in Handwritten Documents (GK, VG), pp. 2041–2046.
ICPRICPR-2014-LeiSLCXP #learning #metric #similarity
Humanoid Robot Imitation with Pose Similarity Metric Learning (JL, MS, ZNL, CC, XX, SP), pp. 4240–4245.
ICPRICPR-2014-LiuL0L #classification #image #learning
Regularized Hierarchical Feature Learning with Non-negative Sparsity and Selectivity for Image Classification (BL, JL, XB, HL), pp. 4293–4298.
ICPRICPR-2014-LiuWCL #automation #category theory #image #learning
Automatic Image Attribute Selection for Zero-Shot Learning of Object Categories (LL, AW, SC, BCL), pp. 2619–2624.
ICPRICPR-2014-LiuYHTH #learning #recognition #visual notation
Semi-supervised Learning for Cross-Device Visual Location Recognition (PL, PY, KH, TT, HWH), pp. 2873–2878.
ICPRICPR-2014-LiuZC #identification #learning #metric #multi #parametricity
Parametric Local Multi-modal Metric Learning for Person Re-identification (KL, ZCZ, AC), pp. 2578–2583.
ICPRICPR-2014-LuoJ #encoding #image #learning #retrieval #semantics
Learning Semantic Binary Codes by Encoding Attributes for Image Retrieval (JL, ZJ), pp. 279–284.
ICPRICPR-2014-ManfrediGC #energy #graph #image #learning #segmentation
Learning Graph Cut Energy Functions for Image Segmentation (MM, CG, RC), pp. 960–965.
ICPRICPR-2014-MarcaciniDHR #approach #clustering #documentation #learning #metric
Privileged Information for Hierarchical Document Clustering: A Metric Learning Approach (RMM, MAD, ERH, SOR), pp. 3636–3641.
ICPRICPR-2014-MontagnerjH #machine learning
A Machine Learning Based Method for Staff Removal (IdSM, RHJ, NSTH), pp. 3162–3167.
ICPRICPR-2014-NegrelPG #image #learning #metric #performance #reduction #retrieval #using
Efficient Metric Learning Based Dimension Reduction Using Sparse Projectors for Image Near Duplicate Retrieval (RN, DP, PHG), pp. 738–743.
ICPRICPR-2014-NieJ #learning #linear #using
Feature Learning Using Bayesian Linear Regression Model (SN, QJ), pp. 1502–1507.
ICPRICPR-2014-NieKZ #learning #recognition #using
Periocular Recognition Using Unsupervised Convolutional RBM Feature Learning (LN, AK, SZ), pp. 399–404.
ICPRICPR-2014-NilufarP #detection #learning #programming
Learning to Detect Contours with Dynamic Programming Snakes (SN, TJP), pp. 984–989.
ICPRICPR-2014-OHarneyMRCSCBF #kernel #learning #multi #pseudo
Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data (ADO, AM, KR, KC, ABS, AC, CB, MF), pp. 3185–3190.
ICPRICPR-2014-PatriciaTC #adaptation #learning #multi #performance
Multi-source Adaptive Learning for Fast Control of Prosthetics Hand (NP, TT, BC), pp. 2769–2774.
ICPRICPR-2014-PengWQP #encoding #evaluation #learning #recognition #taxonomy
A Joint Evaluation of Dictionary Learning and Feature Encoding for Action Recognition (XP, LW, YQ, QP), pp. 2607–2612.
ICPRICPR-2014-PhamKC #graph #image #learning
Semi-supervised Learning on Bi-relational Graph for Image Annotation (HDP, KHK, SC), pp. 2465–2470.
ICPRICPR-2014-PillaiFR #classification #learning #multi
Learning of Multilabel Classifiers (IP, GF, FR), pp. 3452–3456.
ICPRICPR-2014-RenYZH #classification #image #learning #nearest neighbour
Learning Convolutional Nonlinear Features for K Nearest Neighbor Image Classification (WR, YY, JZ, KH), pp. 4358–4363.
ICPRICPR-2014-RiabchenkoKC #generative #learning #modelling
Learning Generative Models of Object Parts from a Few Positive Examples (ER, JKK, KC), pp. 2287–2292.
ICPRICPR-2014-RozzaMP #graph #kernel #learning #novel
A Novel Graph-Based Fisher Kernel Method for Semi-supervised Learning (AR, MM, AP), pp. 3786–3791.
ICPRICPR-2014-SaitoAFRSGC #learning #using
Active Semi-supervised Learning Using Optimum-Path Forest (PTMS, WPA, AXF, PJdR, CTNS, JFG, MHdC), pp. 3798–3803.
ICPRICPR-2014-SatoKSK #classification #learning #multi
Learning Multiple Complex Features Based on Classification Results (YS, KK, YS, MK), pp. 3369–3373.
ICPRICPR-2014-SavakisRP #difference #gesture #learning #using
Gesture Control Using Active Difference Signatures and Sparse Learning (AES, RR, RWP), pp. 3969–3974.
ICPRICPR-2014-ShenHSGM #framework #interactive #learning
Interactive Framework for Insect Tracking with Active Learning (MS, WH, PS, CGG, DM), pp. 2733–2738.
ICPRICPR-2014-StraehleKKH #learning #multi #random
Multiple Instance Learning with Response-Optimized Random Forests (CNS, MK, UK, FAH), pp. 3768–3773.
ICPRICPR-2014-UmakanthanDFS #learning #multi #process #representation #taxonomy
Multiple Instance Dictionary Learning for Activity Representation (SU, SD, CF, SS), pp. 1377–1382.
ICPRICPR-2014-VellankiDVP #learning #parametricity
Nonparametric Discovery of Learning Patterns and Autism Subgroups from Therapeutic Data (PV, TVD, SV, DQP), pp. 1828–1833.
ICPRICPR-2014-WalhaDLGA #approach #image #learning #taxonomy
Sparse Coding with a Coupled Dictionary Learning Approach for Textual Image Super-resolution (RW, FD, FL, CG, AMA), pp. 4459–4464.
ICPRICPR-2014-WangGJ #learning #using
Learning with Hidden Information Using a Max-Margin Latent Variable Model (ZW, TG, QJ), pp. 1389–1394.
ICPRICPR-2014-WangWH #framework #learning #multi #predict #risk management
A Multi-task Learning Framework for Joint Disease Risk Prediction and Comorbidity Discovery (XW, FW, JH), pp. 220–225.
ICPRICPR-2014-WangWJ #learning
Learning with Hidden Information (ZW, XW, QJ), pp. 238–243.
ICPRICPR-2014-WangZWB #learning #modelling
Learning Room Occupancy Patterns from Sparsely Recovered Light Transport Models (QW, XZ, MW, KLB), pp. 1987–1992.
ICPRICPR-2014-WanHA #image #learning #recognition
Indoor Scene Recognition from RGB-D Images by Learning Scene Bases (SW, CH, JKA), pp. 3416–3421.
ICPRICPR-2014-WatanabeW #analysis #component #distance #learning #metric #performance
Logistic Component Analysis for Fast Distance Metric Learning (KW, TW), pp. 1278–1282.
ICPRICPR-2014-WuHYWT #image #network #segmentation
Early Hierarchical Contexts Learned by Convolutional Networks for Image Segmentation (ZW, YH, YY, LW, TT), pp. 1538–1543.
ICPRICPR-2014-WuJ #detection #learning
Learning the Deep Features for Eye Detection in Uncontrolled Conditions (YW, QJ), pp. 455–459.
ICPRICPR-2014-WuLWHJ #learning #multi
Multi-label Learning with Missing Labels (BW, ZL, SW, BGH, QJ), pp. 1964–1968.
ICPRICPR-2014-WuS #learning #multi #recognition
Regularized Multi-view Multi-metric Learning for Action Recognition (XW, SKS), pp. 471–476.
ICPRICPR-2014-WuTS #3d #learning #rank
Learning to Rank the Severity of Unrepaired Cleft Lip Nasal Deformity on 3D Mesh Data (JW, RT, LGS), pp. 460–464.
ICPRICPR-2014-XieUKG #incremental #learning
Incremental Learning with Support Vector Data Description (WX, SU, SK, MG), pp. 3904–3909.
ICPRICPR-2014-XuS #learning #network #using
Bayesian Network Structure Learning Using Causality (ZX, SNS), pp. 3546–3551.
ICPRICPR-2014-YangN #integration #learning #multi
Semi-supervised Learning of Geospatial Objects through Multi-modal Data Integration (YY, SN), pp. 4062–4067.
ICPRICPR-2014-YangXWL #learning #realtime
Real-Time Tracking via Deformable Structure Regression Learning (XY, QX, SW, PL), pp. 2179–2184.
ICPRICPR-2014-YangYH #learning
Diversity-Based Ensemble with Sample Weight Learning (CY, XCY, HWH), pp. 1236–1241.
ICPRICPR-2014-YanSRLS #classification #interactive #learning #multi
Evaluating Multi-task Learning for Multi-view Head-Pose Classification in Interactive Environments (YY, RS, ER, OL, NS), pp. 4182–4187.
ICPRICPR-2014-YiLLL #identification #learning #metric
Deep Metric Learning for Person Re-identification (DY, ZL, SL, SZL), pp. 34–39.
ICPRICPR-2014-YinYPH #case study #classification #learning
Shallow Classification or Deep Learning: An Experimental Study (XCY, CY, WYP, HWH), pp. 1904–1909.
ICPRICPR-2014-YooJKC #learning #optimisation
Transfer Learning of Motion Patterns in Traffic Scene via Convex Optimization (YJY, HJ, SWK, JYC), pp. 4158–4163.
ICPRICPR-2014-ZenRS #distance #learning #matrix #metric
Simultaneous Ground Metric Learning and Matrix Factorization with Earth Mover’s Distance (GZ, ER, NS), pp. 3690–3695.
ICPRICPR-2014-ZhangM14a #detection #learning #multi
Simultaneous Detection of Multiple Facial Action Units via Hierarchical Task Structure Learning (XZ, MHM), pp. 1863–1868.
ICPRICPR-2014-ZhangQWL #classification #learning #online
Object Classification in Traffic Scene Surveillance Based on Online Semi-supervised Active Learning (ZZ, JQ, YW, ML), pp. 3086–3091.
ICPRICPR-2014-ZhouIWBPKO #learning #performance
Transfer Learning of a Temporal Bone Performance Model via Anatomical Feature Registration (YZ, II, SNRW, JB, PP, GK, SO), pp. 1916–1921.
ICPRICPR-2014-ZhuS #learning #recognition #taxonomy
Correspondence-Free Dictionary Learning for Cross-View Action Recognition (FZ, LS), pp. 4525–4530.
ICPRICPR-2014-ZhuWYJ #learning #modelling #multi #recognition #semantics
Multiple-Facial Action Unit Recognition by Shared Feature Learning and Semantic Relation Modeling (YZ, SW, LY, QJ), pp. 1663–1668.
KDDKDD-2014-Bengio #learning #scalability
Scaling up deep learning (YB), p. 1966.
KDDKDD-2014-BensonRS #learning #multi #network #scalability
Learning multifractal structure in large networks (ARB, CR, SS), pp. 1326–1335.
KDDKDD-2014-DalessandroCRPWP #learning #online #scalability
Scalable hands-free transfer learning for online advertising (BD, DC, TR, CP, MHW, FJP), pp. 1573–1582.
KDDKDD-2014-GaddeAO #graph #learning #using
Active semi-supervised learning using sampling theory for graph signals (AG, AA, AO), pp. 492–501.
KDDKDD-2014-GohR #learning
Box drawings for learning with imbalanced data (STG, CR), pp. 333–342.
KDDKDD-2014-GongZFY #learning #multi #performance
Efficient multi-task feature learning with calibration (PG, JZ, WF, JY), pp. 761–770.
KDDKDD-2014-GrabockaSWS #learning
Learning time-series shapelets (JG, NS, MW, LST), pp. 392–401.
KDDKDD-2014-Kushnir #adaptation #kernel #learning
Active-transductive learning with label-adapted kernels (DK), pp. 462–471.
KDDKDD-2014-LanSB #analysis #learning
Time-varying learning and content analytics via sparse factor analysis (ASL, CS, RGB), pp. 452–461.
KDDKDD-2014-LiangRR #learning #personalisation
Personalized search result diversification via structured learning (SL, ZR, MdR), pp. 751–760.
KDDKDD-2014-Mullainathan #machine learning #question #social
Bugbears or legitimate threats?: (social) scientists’ criticisms of machine learning? (SM), p. 4.
KDDKDD-2014-PerozziAS #learning #named #online #social
DeepWalk: online learning of social representations (BP, RAR, SS), pp. 701–710.
KDDKDD-2014-PrabhuV #classification #learning #multi #named #performance
FastXML: a fast, accurate and stable tree-classifier for extreme multi-label learning (YP, MV), pp. 263–272.
KDDKDD-2014-PurushothamMKO #feature model #higher-order #interactive #learning #modelling
Factorized sparse learning models with interpretable high order feature interactions (SP, MRM, CCJK, RO), pp. 552–561.
KDDKDD-2014-QianHJPZ #approach #distance #learning #metric #using
Distance metric learning using dropout: a structured regularization approach (QQ, JH, RJ, JP, SZ), pp. 323–332.
KDDKDD-2014-Rudin #algorithm #machine learning
Algorithms for interpretable machine learning (CR), p. 1519.
KDDKDD-2014-Salakhutdinov #learning
Deep learning (RS), p. 1973.
KDDKDD-2014-ShaoAK #concept #data type #learning #prototype
Prototype-based learning on concept-drifting data streams (JS, ZA, SK), pp. 412–421.
KDDKDD-2014-SrikantA #machine learning #programming #using
A system to grade computer programming skills using machine learning (SS, VA), pp. 1887–1896.
KDDKDD-2014-TayebiEGB #embedded #learning #predict #using
Spatially embedded co-offence prediction using supervised learning (MAT, ME, UG, PLB), pp. 1789–1798.
KDDKDD-2014-VasishtDVK #classification #learning #multi
Active learning for sparse bayesian multilabel classification (DV, ACD, MV, AK), pp. 472–481.
KDDKDD-2014-WangNH #adaptation #induction #learning #scalability
Large-scale adaptive semi-supervised learning via unified inductive and transductive model (DW, FN, HH), pp. 482–491.
KDDKDD-2014-WangSE #collaboration #learning #permutation
Active collaborative permutation learning (JW, NS, JE), pp. 502–511.
KDDKDD-2014-WangSW #learning #modelling
Unsupervised learning of disease progression models (XW, DS, FW), pp. 85–94.
KDDKDD-2014-XuL #behaviour #learning #problem
Product selection problem: improve market share by learning consumer behavior (SX, JCSL), pp. 851–860.
KDDKDD-2014-YangH #learning #parametricity
Learning with dual heterogeneity: a nonparametric bayes model (HY, JH), pp. 582–590.
KDDKDD-2014-ZhangTMF #learning #network
Supervised deep learning with auxiliary networks (JZ, GT, YM, WF), pp. 353–361.
KDDKDD-2014-ZhouC #adaptation #documentation #learning #rank
Unifying learning to rank and domain adaptation: enabling cross-task document scoring (MZ, KCCC), pp. 781–790.
KDIRKDIR-2014-Bleiweiss #execution #machine learning #using
SoC Processor Discovery for Program Execution Matching Using Unsupervised Machine Learning (AB), pp. 192–201.
KDIRKDIR-2014-DistanteCVL #learning #online #paradigm #plugin #topic
Enhancing Online Discussion Forums with a Topic-driven Navigational Paradigm — A Plugin for the Moodle Learning Management System (DD, LC, AV, ML), pp. 97–106.
KDIRKDIR-2014-SuciuICDP #learning #word
Learning Good Opinions from Just Two Words Is Not Bad (DAS, VVI, ACC, MD, RP), pp. 233–241.
KEODKEOD-2014-KarkalasS #concept #learning #modelling #student
Intelligent Student Support in the FLIP Learning System based on Student Initial Misconceptions and Student Modelling (SK, SGS), pp. 353–360.
KMISKMIS-2014-AtrashAM #collaboration #learning
Supporting Organizational Learning with Collaborative Annotation (AA, MHA, CM), pp. 237–244.
KMISKMIS-2014-BartuskovaK #information management #learning
Knowledge Management and Sharing in E-Learning — Hierarchical System for Managing Learning Resources (AB, OK), pp. 179–185.
KMISKMIS-2014-HisakaneOSK #multi
A Tutoring Rule Selection Method for Case-based e-Learning by Multi-class Support Vector Machine (DH, MO, MS, NK), pp. 119–125.
KMISKMIS-2014-HisakaneS #learning #visualisation
A Visualization System of Discussion Structure in Case Method Learning (DH, MS), pp. 126–132.
KMISKMIS-2014-SmirnovS #implementation #information management #lessons learnt
Role-Driven Knowledge Management Implementation — Lessons Learned (AVS, NS), pp. 36–43.
KRKR-2014-KonevLOW #learning #lightweight #logic #ontology
Exact Learning of Lightweight Description Logic Ontologies (BK, CL, AO, FW).
KRKR-2014-Michael #learning #predict
Simultaneous Learning and Prediction (LM).
MLDMMLDM-2014-AlbarrakCZ #classification #image #taxonomy
Dictionary Learning-Based Volumetric Image Classification for the Diagnosis of Age-Related Macular Degeneration (AA, FC, YZ), pp. 272–284.
MLDMMLDM-2014-BugaychenkoZ #diagrams #learning #multi #pattern matching #pattern recognition #performance #recognition #using
Fast Pattern Recognition and Deep Learning Using Multi-Rooted Binary Decision Diagrams (DB, DZ), pp. 73–77.
MLDMMLDM-2014-KhasnabishSDS #detection #learning #programming language #source code #using
Detecting Programming Language from Source Code Using Bayesian Learning Techniques (JNK, MS, JD, GS), pp. 513–522.
MLDMMLDM-2014-KuleshovB #data mining #learning #mining
Manifold Learning in Data Mining Tasks (APK, AVB), pp. 119–133.
MLDMMLDM-2014-NeumannHRL #case study #experience #learning
A Robot Waiter Learning from Experiences (BN, LH, PR, JL), pp. 285–299.
MLDMMLDM-2014-SandovalH #learning #network #using
Learning of Natural Trading Strategies on Foreign Exchange High-Frequency Market Data Using Dynamic Bayesian Networks (JS, GH), pp. 408–421.
RecSysRecSys-2014-BhagatWIT #learning #matrix #recommendation #using
Recommending with an agenda: active learning of private attributes using matrix factorization (SB, UW, SI, NT), pp. 65–72.
RecSysRecSys-2014-KrishnanPFG #bias #learning #recommendation #social
A methodology for learning, analyzing, and mitigating social influence bias in recommender systems (SK, JP, MJF, KG), pp. 137–144.
RecSysRecSys-2014-SaveskiM #learning #recommendation
Item cold-start recommendations: learning local collective embeddings (MS, AM), pp. 89–96.
SEKESEKE-2014-GaoKN #estimation #learning #quality #ranking
Comparing Two Approaches for Adding Feature Ranking to Sampled Ensemble Learning for Software Quality Estimation (KG, TMK, AN), pp. 280–285.
SEKESEKE-2014-JuniorFJB #learning #mobile #product line #towards
Towards the Establishment of a Software Product Line for Mobile Learning Applications (VFJ, NFDF, EAdOJ, EFB), pp. 678–683.
SEKESEKE-2014-SantosBSC #game studies #learning #programming #semantics #source code
A Semantic Analyzer for Simple Games Source Codes to Programming Learning (ECOdS, GBB, VHVdS, EC), pp. 522–527.
SEKESEKE-2014-SinghS #machine learning #requirements #using
Software Requirement Prioritization using Machine Learning (DS, AS), pp. 701–704.
SIGIRSIGIR-2014-CanCM #feedback #modelling #ranking
Incorporating query-specific feedback into learning-to-rank models (EFC, WBC, RM), pp. 1035–1038.
SIGIRSIGIR-2014-CormackG #bibliography #evaluation #protocol
Evaluation of machine-learning protocols for technology-assisted review in electronic discovery (GVC, MRG), pp. 153–162.
SIGIRSIGIR-2014-CostaCS #learning #modelling #ranking
Learning temporal-dependent ranking models (MC, FMC, MJS), pp. 757–766.
SIGIRSIGIR-2014-EfronWS #learning #query
Learning sufficient queries for entity filtering (ME, CW, GS), pp. 1091–1094.
SIGIRSIGIR-2014-FangWYZ #information retrieval #learning #modelling #named
VIRLab: a web-based virtual lab for learning and studying information retrieval models (HF, HW, PY, CZ), pp. 1249–1250.
SIGIRSIGIR-2014-JiangKCC #behaviour #learning #query
Learning user reformulation behavior for query auto-completion (JYJ, YYK, PYC, PJC), pp. 445–454.
SIGIRSIGIR-2014-LengCL #image #learning #random #retrieval #scalability
Random subspace for binary codes learning in large scale image retrieval (CL, JC, HL), pp. 1031–1034.
SIGIRSIGIR-2014-LiuL #learning #probability #segmentation #word
Probabilistic ensemble learning for vietnamese word segmentation (WL, LL), pp. 931–934.
SIGIRSIGIR-2014-NiuLGCG #data analysis #learning #rank #robust #what
What makes data robust: a data analysis in learning to rank (SN, YL, JG, XC, XG), pp. 1191–1194.
SIGIRSIGIR-2014-PanYMLNR #image #learning
Click-through-based cross-view learning for image search (YP, TY, TM, HL, CWN, YR), pp. 717–726.
SIGIRSIGIR-2014-QiuCYLL #learning #personalisation #ranking
Item group based pairwise preference learning for personalized ranking (SQ, JC, TY, CL, HL), pp. 1219–1222.
SIGIRSIGIR-2014-SokolovHR #learning #query
Learning to translate queries for CLIR (AS, FH, SR), pp. 1179–1182.
SIGIRSIGIR-2014-SpinaGA #detection #learning #monitoring #online #similarity #topic
Learning similarity functions for topic detection in online reputation monitoring (DS, JG, EA), pp. 527–536.
SIGIRSIGIR-2014-UstaAVOU #analysis #education #how #learning #student
How k-12 students search for learning?: analysis of an educational search engine log (AU, ISA, IBV, RO, ÖU), pp. 1151–1154.
SIGIRSIGIR-2014-VulicZM #e-commerce #formal method #learning
Learning to bridge colloquial and formal language applied to linking and search of E-Commerce data (IV, SZ, MFM), pp. 1195–1198.
SIGIRSIGIR-2014-WuMHR #image #learning #personalisation
Learning to personalize trending image search suggestion (CCW, TM, WHH, YR), pp. 727–736.
SIGIRSIGIR-2014-YuWZTSZ #learning #rank
Hashing with List-Wise learning to rank (ZY, FW, YZ, ST, JS, YZ), pp. 999–1002.
SIGIRSIGIR-2014-ZhuLGCN #learning
Learning for search result diversification (YZ, YL, JG, XC, SN), pp. 293–302.
SIGIRSIGIR-2014-ZhuNG #adaptation #learning #random #social
An adaptive teleportation random walk model for learning social tag relevance (XZ, WN, MG), pp. 223–232.
MODELSMoDELS-2014-BakiSCMF #learning #model transformation
Learning Implicit and Explicit Control in Model Transformations by Example (IB, HAS, QC, PM, MF), pp. 636–652.
MODELSMoDELS-2014-RabiserVGDSL #case study #experience #lessons learnt #modelling #multi
Supporting Multiplicity and Hierarchy in Model-Based Configuration: Experiences and Lessons Learned (RR, MV, PG, DD, HS, ML), pp. 320–336.
MODELSMoDELS-2014-BakiSCMF #learning #model transformation
Learning Implicit and Explicit Control in Model Transformations by Example (IB, HAS, QC, PM, MF), pp. 636–652.
MODELSMoDELS-2014-RabiserVGDSL #case study #experience #lessons learnt #modelling #multi
Supporting Multiplicity and Hierarchy in Model-Based Configuration: Experiences and Lessons Learned (RR, MV, PG, DD, HS, ML), pp. 320–336.
RERE-2014-MaalejG #lessons learnt
Capturing and sharing domain knowledge with business rules lessons learned from a global software vendor (WM, SG), pp. 364–373.
SACSAC-2014-ChallcoI #authoring #design #learning #personalisation #towards
Towards a learning design authoring tool that generates personalized units of learning for CSCL (GCC, SI), pp. 778–780.
SACSAC-2014-DhanjalC #learning #network
Learning reputation in an authorship network (CD, SC), pp. 1724–1726.
SACSAC-2014-LiWL #learning #mobile #online #recognition
Online learning with mobile sensor data for user recognition (HGL, XW, ZL), pp. 64–70.
SACSAC-2014-PaivaBSBS #case study #lessons learnt #online
Lessons learned from an online open course: a Brazilian case study (ROAP, DB, JS, IIB, APdS), pp. 229–234.
SACSAC-2014-PessinOUWMV #evolution #learning #network #self
Self-localisation in indoor environments combining learning and evolution with wireless networks (GP, FSO, JU, DFW, RCM, PAV), pp. 661–666.
FSEFSE-2014-AllamanisBBS #learning
Learning natural coding conventions (MA, ETB, CB, CAS), pp. 281–293.
FSEFSE-2014-Joseph #framework #interactive #machine learning
Software programmer management: a machine learning and human computer interaction framework for optimal task assignment (HRJ), pp. 826–828.
FSEFSE-2014-YeBL #debugging #learning #rank #using
Learning to rank relevant files for bug reports using domain knowledge (XY, RCB, CL), pp. 689–699.
ICSEICSE-2014-HeWYZ #learning #reasoning
Symbolic assume-guarantee reasoning through BDD learning (FH, BYW, LY, LZ), pp. 1071–1082.
ICSEICSE-2014-JingYZWL #fault #learning #predict #taxonomy
Dictionary learning based software defect prediction (XYJ, SY, ZWZ, SSW, JL), pp. 414–423.
ICSEICSE-2014-LeeJP #behaviour #detection #machine learning #memory management #modelling #using
Detecting memory leaks through introspective dynamic behavior modelling using machine learning (SL, CJ, SP), pp. 814–824.
ICSEICSE-2014-Monperrus #automation #bibliography #evaluation #generative #problem
A critical review of “automatic patch generation learned from human-written patches”: essay on the problem statement and the evaluation of automatic software repair (MM), pp. 234–242.
ASPLOSASPLOS-2014-ChenDSWWCT #named #ubiquitous
DianNao: a small-footprint high-throughput accelerator for ubiquitous machine-learning (TC, ZD, NS, JW, CW, YC, OT), pp. 269–284.
HPCAHPCA-2014-WonCGHS #learning #network #online #power management
Up by their bootstraps: Online learning in Artificial Neural Networks for CMP uncore power management (JYW, XC, PG, JH, VS), pp. 308–319.
OSDIOSDI-2014-ChilimbiSAK #learning #performance #scalability
Project Adam: Building an Efficient and Scalable Deep Learning Training System (TMC, YS, JA, KK), pp. 571–582.
OSDIOSDI-2014-LiAPSAJLSS #distributed #machine learning #parametricity #scalability
Scaling Distributed Machine Learning with the Parameter Server (ML, DGA, JWP, AJS, AA, VJ, JL, EJS, BYS), pp. 583–598.
CAVCAV-2014-0001LMN #framework #invariant #learning #named #robust
ICE: A Robust Framework for Learning Invariants (PG, CL, PM, DN), pp. 69–87.
CAVCAV-2014-HeizmannHP #analysis #learning #source code #termination
Termination Analysis by Learning Terminating Programs (MH, JH, AP), pp. 797–813.
SMTSMT-2014-KorovinKS #learning #towards
Towards Conflict-Driven Learning for Virtual Substitution (KK, MK, TS), p. 71.
ASEASE-2013-DietrichCS #effectiveness #learning #query #requirements #retrieval
Learning effective query transformations for enhanced requirements trace retrieval (TD, JCH, YS), pp. 586–591.
ASEASE-2013-GuoCASW #approach #learning #performance #predict #statistics #variability
Variability-aware performance prediction: A statistical learning approach (JG, KC, SA, NS, AW), pp. 301–311.
ASEASE-2013-Xiao0LLS #learning #named #type system
TzuYu: Learning stateful typestates (HX, JS, YL, SWL, CS), pp. 432–442.
CASECASE-2013-LiX #adaptation #learning
Off-line learning based adaptive dispatching rule for semiconductor wafer fabrication facility (LL, HX), pp. 1028–1033.
CASECASE-2013-OFlahertyE #bound #learning #sequence
Learning to locomote: Action sequences and switching boundaries (RO, ME), pp. 7–12.
CASECASE-2013-SharabianiDBCND #machine learning #predict
Machine learning based prediction of warfarin optimal dosing for African American patients (AS, HD, AB, LC, EN, KD), pp. 623–628.
DACDAC-2013-LiuC #on the #synthesis
On learning-based methods for design-space exploration with high-level synthesis (HYL, LPC), p. 7.
DACDAC-2013-YuLJC #classification #detection #feature model #using
Machine-learning-based hotspot detection using topological classification and critical feature extraction (YTY, GHL, IHRJ, CC), p. 6.
DATEDATE-2013-DeOrioLBB #debugging #detection #machine learning
Machine learning-based anomaly detection for post-silicon bug diagnosis (AD, QL, MB, VB), pp. 491–496.
DATEDATE-2013-QianJBTMM #analysis #named #performance #using
SVR-NoC: a performance analysis tool for network-on-chips using learning-based support vector regression model (ZQ, DCJ, PB, CYT, DM, RM), pp. 354–357.
DocEngDocEng-2013-DoTT #documentation #taxonomy #using
Document noise removal using sparse representations over learned dictionary (THD, ST, ORT), pp. 161–168.
DocEngDocEng-2013-Esposito #documentation #machine learning
Symbolic machine learning methods for historical document processing (FE), pp. 1–2.
ICDARICDAR-2013-AgarwalGC #learning
Greedy Search for Active Learning of OCR (AA, RG, SC), pp. 837–841.
ICDARICDAR-2013-BougueliaBB #approach #classification #documentation #learning
A Stream-Based Semi-supervised Active Learning Approach for Document Classification (MRB, YB, AB), pp. 611–615.
ICDARICDAR-2013-BouillonLAR #gesture #learning #using
Using Confusion Reject to Improve (User and) System (Cross) Learning of Gesture Commands (MB, PL, ÉA, GR), pp. 1017–1021.
ICDARICDAR-2013-KasarBACP #detection #documentation #image #learning #using
Learning to Detect Tables in Scanned Document Images Using Line Information (TK, PB, SA, CC, TP), pp. 1185–1189.
ICDARICDAR-2013-LvHWL #online #realtime #recognition #segmentation
Learning-Based Candidate Segmentation Scoring for Real-Time Recognition of Online Overlaid Chinese Handwriting (YFL, LLH, DHW, CLL), pp. 74–78.
ICDARICDAR-2013-NguyenCBO #image #interactive #learning
Interactive Knowledge Learning for Ancient Images (NVN, MC, AB, JMO), pp. 300–304.
ICDARICDAR-2013-PuriST #learning #network
Bayesian Network Structure Learning and Inference Methods for Handwriting (MP, SNS, YT), pp. 1320–1324.
ICDARICDAR-2013-SchambachR #learning #network #sequence
Stabilize Sequence Learning with Recurrent Neural Networks by Forced Alignment (MPS, SFR), pp. 1270–1274.
ICDARICDAR-2013-SuL #learning #recognition
Discriminative Weighting and Subspace Learning for Ensemble Symbol Recognition (FS, TL), pp. 1088–1092.
ICDARICDAR-2013-SuTLDT #classification #documentation #image #learning #representation
Self Learning Classification for Degraded Document Images by Sparse Representation (BS, ST, SL, TAD, CLT), pp. 155–159.
ICDARICDAR-2013-TeradaHFU #detection #on the
On the Possibility of Structure Learning-Based Scene Character Detector (YT, RH, YF, SU), pp. 472–476.
ICDARICDAR-2013-TuarobBMG #automation #detection #documentation #machine learning #pseudo #using
Automatic Detection of Pseudocodes in Scholarly Documents Using Machine Learning (ST, SB, PM, CLG), pp. 738–742.
ICDARICDAR-2013-WalhaDLGA #clustering #image #multi
Multiple Learned Dictionaries Based Clustered Sparse Coding for the Super-Resolution of Single Text Image (RW, FD, FL, CG, AMA), pp. 484–488.
ICDARICDAR-2013-ZhouYL #learning #performance #polynomial #recognition
GPU-Based Fast Training of Discriminative Learning Quadratic Discriminant Function for Handwritten Chinese Character Recognition (MKZ, FY, CLL), pp. 842–846.
ICDARICDAR-2013-Zhu0N #learning #recognition
Sub-structure Learning Based Handwritten Chinese Text Recognition (YZ, JS, SN), pp. 295–299.
PODSPODS-2013-AbouziedAPHS #learning #quantifier #query #verification
Learning and verifying quantified boolean queries by example (AA, DA, CHP, JMH, AS), pp. 49–60.
SIGMODSIGMOD-2013-CondieMPW #big data #machine learning
Machine learning for big data (TC, PM, NP, MW), pp. 939–942.
SIGMODSIGMOD-2013-MullerKLM #named #what
WOW: what the world of (data) warehousing can learn from the World of Warcraft (RM, TK, GML, JM), pp. 961–964.
VLDBVLDB-2013-BergamaschiGILV #data-driven #database #keyword #machine learning #named #relational #semantics
QUEST: A Keyword Search System for Relational Data based on Semantic and Machine Learning Techniques (SB, FG, MI, RTL, YV), pp. 1222–1225.
VLDBVLDB-2013-BrunatoB #learning #optimisation
Learning and Intelligent Optimization (LION): One Ring to Rule Them All (MB, RB), pp. 1176–1177.
VLDBVLDB-2013-Hoppe #automation #big data #learning #ontology #web
Automatic ontology-based User Profile Learning from heterogeneous Web Resources in a Big Data Context (AH), pp. 1428–1433.
VLDBVLDB-2013-ZhouTWN #2d #learning #named #predict #probability
R2-D2: a System to Support Probabilistic Path Prediction in Dynamic Environments via “Semi-Lazy” Learning (JZ, AKHT, WW, WSN), pp. 1366–1369.
CSEETCSEET-2013-ChimalakondaN #adaptation #education #learning #personalisation #re-engineering #what
What makes it hard to teach software engineering to end users? some directions from adaptive and personalized learning (SC, KVN), pp. 324–328.
CSEETCSEET-2013-Georgas #composition #design #education #learning #towards
Toward infusing modular and reflective design learning throughout the curriculum (JCG), pp. 274–278.
CSEETCSEET-2013-RibaudS #cost analysis #information management #learning #problem
The cost of problem-based learning: An example in information systems engineering (VR, PS), pp. 259–263.
CSEETCSEET-2013-StejskalS #learning #testing
Test-driven learning in high school computer science (RS, HPS), pp. 289–293.
CSEETCSEET-2013-Vallino #question #re-engineering #student #what
What should students learn in their first (and often only) software engineering course? (JV), pp. 335–337.
ITiCSEITiCSE-2013-Alshaigy #development #education #interactive #learning #programming language #python
Development of an interactive learning tool to teach python programming language (BA), p. 344.
ITiCSEITiCSE-2013-BeltranGP #architecture #concept #in the cloud #using
Using CloudSim to learn cloud computing architecture/system concepts in a graduate course (MB, AG, MP), pp. 82–87.
ITiCSEITiCSE-2013-CalvoGII #content management #evaluation #heuristic #learning
Are chats and forums accessible in e-learning systems?: a heuristic evaluation comparing four learning content management systems (RC, AG, BI, AI), p. 342.
ITiCSEITiCSE-2013-FernandesCB #learning
A pilot project on non-conventional learning (SF, AC, LSB), p. 346.
ITiCSEITiCSE-2013-German #learning
Jump-starting team-based learning in the computer science classroom (DAG), p. 323.
ITiCSEITiCSE-2013-GorlatovaSKKZ #learning #research #scalability
Project-based learning within a large-scale interdisciplinary research effort (MG, JS, PRK, IK, GZ), pp. 207–212.
ITiCSEITiCSE-2013-HawthorneC #learning #source code
ACM core IT learning outcomes for associate-degree programs (EKH, RDC), p. 357.
ITiCSEITiCSE-2013-JalilPWL #design #interactive #learning #taxonomy
Design eye: an interactive learning environment based on the solo taxonomy (SAJ, BP, IW, ALR), pp. 22–27.
ITiCSEITiCSE-2013-JohnsonCH #contest #development #game studies #learning
Learning elsewhere: tales from an extracurricular game development competition (CJ, AC, SH), pp. 70–75.
ITiCSEITiCSE-2013-MedinaPGR #data mining #education #learning #mining #programming #using
Assistance in computer programming learning using educational data mining and learning analytics (CFM, JRPP, VMÁG, MdPPR), pp. 237–242.
ITiCSEITiCSE-2013-MellodgeR #arduino #case study #experience #framework #learning #student #using
Using the arduino platform to enhance student learning experiences (PM, IR), p. 338.
ITiCSEITiCSE-2013-Paule-RuizGPG #evaluation #framework #interactive #learning
Voice interactive learning: a framework and evaluation (MPPR, VMÁG, JRPP, MRG), pp. 34–39.
ITiCSEITiCSE-2013-QianYGBT #authentication #learning #mobile #network #security
Mobile device based authentic learning for computer network and security (KQ, MY, MG, PB, LT), p. 335.
ITiCSEITiCSE-2013-ReedZ #framework #learning
A hierarchical framework for mapping and quantitatively assessing program and learning outcomes (JR, HZ), pp. 52–57.
ITiCSEITiCSE-2013-RowanD #bibliography #learning #mobile #using
A systematic literature review on using mobile computing as a learning intervention (MR, JD), p. 339.
ITiCSEITiCSE-2013-Sanchez-Nielsen #learning #multi #student
Producing multimedia pills to stimulate student learning and engagement (ESN), pp. 165–170.
ITiCSEITiCSE-2013-ScottG #learning #programming #question
Implicit theories of programming aptitude as a barrier to learning to code: are they distinct from intelligence? (MJS, GG), p. 347.
ITiCSEITiCSE-2013-ShiQC #adaptation #design #personalisation #social
Designing social personalized adaptive e-learning (LS, DAQ, AIC), p. 341.
ITiCSEITiCSE-2013-VihavainenVLP #learning #student #using
Scaffolding students’ learning using test my code (AV, TV, ML, MP), pp. 117–122.
ITiCSEITiCSE-2013-Wildsmith #learning #named
Kinetic: a learning environment within business (CW), p. 3.
TACASTACAS-2013-ChenW #algorithm #learning #library #named
BULL: A Library for Learning Algorithms of Boolean Functions (YFC, BYW), pp. 537–542.
TACASTACAS-2013-WhiteL #data type #evolution #identification #in memory #learning #memory management
Identifying Dynamic Data Structures by Learning Evolving Patterns in Memory (DHW, GL), pp. 354–369.
CSMRCSMR-2013-MinelliL #lessons learnt #mobile
Software Analytics for Mobile Applications-Insights & Lessons Learned (RM, ML), pp. 144–153.
CSMRCSMR-2013-XiaLWYLS #algorithm #case study #comparative #debugging #learning #predict
A Comparative Study of Supervised Learning Algorithms for Re-opened Bug Prediction (XX, DL, XW, XY, SL, JS), pp. 331–334.
ICSMEICSM-2013-FontanaZMM #approach #detection #machine learning #smell #towards
Code Smell Detection: Towards a Machine Learning-Based Approach (FAF, MZ, AM, MM), pp. 396–399.
ICSMEICSM-2013-OsmanCP #algorithm #analysis #diagrams #machine learning
An Analysis of Machine Learning Algorithms for Condensing Reverse Engineered Class Diagrams (MHO, MRVC, PvdP), pp. 140–149.
ICSMEICSM-2013-Perez #design #lessons learnt #refactoring #smell #summary
Refactoring Planning for Design Smell Correction: Summary, Opportunities and Lessons Learned (JP), pp. 572–577.
ICSMEICSM-2013-SemenenkoDS #image #machine learning #named #testing
Browserbite: Accurate Cross-Browser Testing via Machine Learning over Image Features (NS, MD, TS), pp. 528–531.
ICSMEICSM-2013-SiebraMSS #framework
The Adventure of Developing a Software Application on a Pre-release Platform: Features and Learned Lessons (CdS, AM, FQBdS, ALMS), pp. 556–559.
ICSMEICSM-2013-SorOTS #approach #detection #machine learning #memory management #statistics #using
Improving Statistical Approach for Memory Leak Detection Using Machine Learning (VS, PO, TT, SNS), pp. 544–547.
WCREWCRE-2013-KhadkaSJHH #challenge #legacy #lessons learnt #migration #scalability
Migrating a large scale legacy application to SOA: Challenges and lessons learned (RK, AS, SJ, JH, GPH), pp. 425–432.
WCREWCRE-2013-MontandonBFV #api #framework #lessons learnt
Documenting APIs with examples: Lessons learned with the APIMiner platform (JEM, HB, DF, MTV), pp. 401–408.
SASSAS-2013-0001GHAN #concept #geometry #learning #verification
Verification as Learning Geometric Concepts (RS, SG, BH, AA, AVN), pp. 388–411.
STOCSTOC-2013-BrakerskiLPRS #fault #learning
Classical hardness of learning with errors (ZB, AL, CP, OR, DS), pp. 575–584.
DLTDLT-2013-BolligHLM #approach #automaton #learning
A Fresh Approach to Learning Register Automata (BB, PH, ML, BM), pp. 118–130.
ICALPICALP-v2-2013-FuscoPP #learning #performance
Learning a Ring Cheaply and Fast (EGF, AP, RP), pp. 557–568.
LATALATA-2013-BjorklundFK #automaton #learning
MAT Learning of Universal Automata (JB, HF, AK), pp. 141–152.
GT-VMTGT-VMT-2013-AlshanqitiHK #graph transformation #learning
Learning Minimal and Maximal Rules from Observations of Graph Transformations (AMA, RH, TAK).
CHICHI-2013-AndersonB #gesture #learning #performance
Learning and performance with gesture guides (FA, WFB), pp. 1109–1118.
CHICHI-2013-EdgeCW #learning #named
SpatialEase: learning language through body motion (DE, KYC, MW), pp. 469–472.
CHICHI-2013-HarpsteadMA #data analysis #education #game studies #learning
In search of learning: facilitating data analysis in educational games (EH, BAM, VA), pp. 79–88.
CHICHI-2013-KharrufaBHLDO #deployment #lessons learnt #multi #scalability
Tables in the wild: lessons learned from a large-scale multi-tabletop deployment (AK, MB, PH, DL, PD, PO), pp. 1021–1030.
CHICHI-2013-RauARR #design #interactive #learning #why
Why interactive learning environments can have it all: resolving design conflicts between competing goals (MAR, VA, NR, SR), pp. 109–118.
CHICHI-2013-SzafirM #adaptation #bibliography #learning #named
ARTFul: adaptive review technology for flipped learning (DS, BM), pp. 1001–1010.
CSCWCSCW-2013-KowY #community #learning
Media technologies and learning in the starcraft esport community (YMK, TY), pp. 387–398.
CSCWCSCW-2013-LinF #learning #network
Opportunities via extended networks for teens’ informal learning (PL, SDF), pp. 1341–1352.
HCIDHM-HB-2013-NakamuraKOOHNAKMK #artificial reality #learning #self #student #towards #using
The Relationship between Nursing Students’ Attitudes towards Learning and Effects of Self-learning System Using Kinect (MN, YK, JO, TO, ZH, AN, KA, NK, JM, MKP), pp. 111–116.
HCIDUXU-CXC-2013-BlanklBH #development #human-computer #lessons learnt
Lessons Learned from Projects in Japan and Korea Relevant for Intercultural HCI Development (MB, PB, RH), pp. 20–27.
HCIDUXU-CXC-2013-ChoensawatSKH #education #learning
Desirability of a Teaching and Learning Tool for Thai Dance Body Motion (WC, KS, CK, KH), pp. 171–179.
HCIDUXU-CXC-2013-LeraAVG #experience #user interface
Improving User Experience in e-Learning, the Case of the Open University of Catalonia (EdL, MA, LV, MG), pp. 180–188.
HCIDUXU-CXC-2013-MarchettiB #game studies #learning
Setting Conditions for Learning: Mediated Play and Socio-material Dialogue (EM, EPB), pp. 238–246.
HCIDUXU-CXC-2013-MarcusPL #design #learning #mobile #persuasion #user interface
The Learning Machine: Mobile UX Design That Combines Information Design with Persuasion Design (AM, YP, NL), pp. 247–256.
HCIDUXU-CXC-2013-MouraVCBSTLK #exclamation #game studies #how #learning #mobile
Luz, Câmera, Libras!: How a Mobile Game Can Improve the Learning of Sign Languages (GdSM, LAV, AC, FB, DdS, JMXNT, CWML, JK), pp. 266–275.
HCIDUXU-WM-2013-GencerBZV #framework #machine learning #mobile #using
A New Framework for Increasing User Engagement in Mobile Applications Using Machine Learning Techniques (MG, GB, ÖZ, TV), pp. 651–659.
HCIDUXU-WM-2013-SasajimaNKHHNTTM #learning #ontology
CHARM Pad: Ontology-Based Tool for Learning Systematic Knowledge about Nursing (MS, SN, YK, AH, KH, AN, HT, YT, RM), pp. 560–567.
HCIDUXU-WM-2013-WilkinsonLC #experience #interactive #learning
Exploring Prior Experience and the Effects of Age on Product Interaction and Learning (CRW, PL, PJC), pp. 457–466.
HCIHCI-AMTE-2013-AkiyoshiT #estimation #eye tracking #framework #interface #learning #using
An Estimation Framework of a User Learning Curve on Web-Based Interface Using Eye Tracking Equipment (MA, HT), pp. 159–165.
HCIHCI-AS-2013-AndujarEGM #learning
Evaluating Engagement Physiologically and Knowledge Retention Subjectively through Two Different Learning Techniques (MA, JIE, JEG, PM), pp. 335–342.
HCIHCI-AS-2013-BitontoLRR #collaboration #process #recommendation
Recommendation of Collaborative Activities in E-learning Environments (PDB, ML, TR, VR), pp. 484–492.
HCIHCI-AS-2013-CharoenpitO #biology #using
A New E-learning System Focusing on Emotional Aspect Using Biological Signals (SC, MO), pp. 343–350.
HCIHCI-AS-2013-EskildsenR #challenge #integration #learning
Challenges for Contextualizing Language Learning — Supporting Cultural Integration (SE, MR), pp. 361–369.
HCIHCI-AS-2013-FrajhofACLLM #collaboration #framework #learning #network #social #student #usability
Usability of a Social Network as a Collaborative Learning Platform Tool for Medical Students (LF, ACCA, ATdSC, CJPdL, CAPdL, CRM), pp. 370–375.
HCIHCI-AS-2013-GotodaSMNM #learning #process #realtime
A Server-Based System Supporting Motor Learning through Real-Time and Reflective Learning Activities (NG, YS, KM, KN, CM), pp. 84–93.
HCIHCI-AS-2013-HarunBON #learning #using
Refining Rules Learning Using Evolutionary PD (AFH, SB, CO, NLMN), pp. 376–385.
HCIHCI-AS-2013-HuangC13a #education #interface #learning #music #self #visualisation
Sound to Sight: The Effects of Self-generated Visualization on Music Sight-Singing as an Alternate Learning Interface for Music Education within a Web-Based Environment (YTH, CNC), pp. 386–390.
HCIHCI-AS-2013-LekkasGTMS #behaviour #component #experience #how #learning #process
Personality and Emotion as Determinants of the Learning Experience: How Affective Behavior Interacts with Various Components of the Learning Process (ZL, PG, NT, CM, GS), pp. 418–427.
HCIHCI-AS-2013-LimaRSBSO #learning
Innovation in Learning — The Use of Avatar for Sign Language (TL, MSR, TAS, AB, ES, HSdO), pp. 428–433.
HCIHCI-AS-2013-MajimaMSS #learning
A Proposal of the New System Model for Nursing Skill Learning Based on Cognition and Technique (YM, YM, MS, MS), pp. 134–143.
HCIHCI-AS-2013-MarsicoST #framework #personalisation
A Framework to Support Social-Collaborative Personalized e-Learning (MDM, AS, MT), pp. 351–360.
HCIHCI-AS-2013-MatsumotoAK #development #email #learning #using #word
Development of Push-Based English Words Learning System by Using E-Mail Service (SM, MA, TK), pp. 444–453.
HCIHCI-AS-2013-MbathaM #experience #learning #named
E-learning: The Power Source of Transforming the Learning Experience in an ODL Landscape (BM, MM), pp. 454–463.
HCIHCI-AS-2013-NouriCZ #case study #collaboration #learning #mobile #performance
Mobile Inquiry-Based Learning — A Study of Collaborative Scaffolding and Performance (JN, TCP, KZ), pp. 464–473.
HCIHCI-AS-2013-TakanoS #learning
Nature Sound Ensemble Learning in Narrative-Episode Creation with Pictures (KT, SS), pp. 493–502.
HCIHCI-AS-2013-TogawaK #framework
Private Cloud Cooperation Framework for Reducing the Earthquake Damage on e-Learning Environment (ST, KK), pp. 503–510.
HCIHCI-III-2013-StorzRMLE #analysis #detection #machine learning #visualisation #workflow
Annotate. Train. Evaluate. A Unified Tool for the Analysis and Visualization of Workflows in Machine Learning Applied to Object Detection (MS, MR, RM, HL, ME), pp. 196–205.
HCIHCI-IMT-2013-DruryPKL #design #lessons learnt #visualisation
Decision Space Visualization: Lessons Learned and Design Principles (JLD, MSP, GLK, YL), pp. 658–667.
HCIHCI-UC-2013-LinHW #learning #using #visual notation
Establishing a Cognitive Map of Public Place for Blind and Visual Impaired by Using IVEO Hands-On Learning System (QWL, SLH, JLW), pp. 193–198.
HCIHCI-UC-2013-StarySF #interactive #learning
Agility Based on Stakeholder Interaction — Blending Organizational Learning with Interactive BPM (CS, WS, AF), pp. 456–465.
HCIHIMI-D-2013-TakemoriYST #interactive #learning #modelling #process
Modeling a Human’s Learning Processes to Support Continuous Learning on Human Computer Interaction (KT, TY, KS, KT), pp. 555–564.
HCIHIMI-HSM-2013-HiyamaOMESH #artificial reality #learning
Augmented Reality System for Measuring and Learning Tacit Artisan Skills (AH, HO, MM, EE, MS, MH), pp. 85–91.
HCIHIMI-HSM-2013-SaitohI #detection #learning #using #visualisation
Visualization of Anomaly Data Using Peculiarity Detection on Learning Vector Quantization (FS, SI), pp. 181–188.
HCIHIMI-LCCB-2013-Canter #hybrid #student
A Hybrid Model for an E-learning System Which Develops Metacognitive Skills at Students (MC), pp. 9–15.
HCIHIMI-LCCB-2013-Frederick-RecascinoLDKL #case study #game studies #learning
Articulating an Experimental Model for the Study of Game-Based Learning (CFR, DL, SD, JPK, DL), pp. 25–32.
HCIHIMI-LCCB-2013-HallLS #assessment #evaluation #learning #tool support
Psychophysiological Assessment Tools for Evaluation of Learning Technologies (RHH, NSL, HS), pp. 33–42.
HCIHIMI-LCCB-2013-HayashiON #collaboration #interactive #learning
An Experimental Environment for Analyzing Collaborative Learning Interaction (YH, YO, YIN), pp. 43–52.
HCIHIMI-LCCB-2013-KanamoriTA #development #learning #programming
Development of a Computer Programming Learning Support System Based on Reading Computer Program (HK, TT, TA), pp. 63–69.
HCIHIMI-LCCB-2013-NakajimaT #generative #learning #online
New Potential of E-learning by Re-utilizing Open Content Online — TED NOTE: English Learning System as an Auto-assignment Generator (AN, KT), pp. 108–117.
HCIHIMI-LCCB-2013-WatabeMH #process
Application to Help Learn the Process of Transforming Mathematical Expressions with a Focus on Study Logs (TW, YM, YH), pp. 157–164.
HCIHIMI-LCCB-2013-YamamotoKYMH #learning #online #problem
Learning by Problem-Posing with Online Connected Media Tablets (SY, TK, YY, KM, TH), pp. 165–174.
HCIHIMI-LCCB-2013-YuL #approach #feedback #mining
Exploring User Feedback of a E-Learning System: A Text Mining Approach (WBY, RL), pp. 182–191.
HCIOCSC-2013-Eustace #learning #network
Building and Sustaining a Lifelong Adult Learning Network (KE), pp. 260–268.
HCIOCSC-2013-StieglitzES #behaviour #education #learning #student
Influence of Monetary and Non-monetary Incentives on Students’ Behavior in Blended Learning Settings in Higher Education (SS, AE, MS), pp. 104–112.
VISSOFTVISSOFT-2013-Wijk #case study #experience #lessons learnt #visualisation
Keynote talk: Information visualization: Experiences and lessons learned (JJvW), p. 1.
EDOCEDOC-2013-Swenson #design #learning
Designing for an Innovative Learning Organization (KDS), pp. 209–213.
ICEISICEIS-J-2013-KalsingITN13a #incremental #legacy #mining #modelling #process #using
Re-learning of Business Process Models from Legacy System Using Incremental Process Mining (ACK, CI, LHT, GSdN), pp. 314–330.
ICEISICEIS-v2-2013-EomA #testing
Developing and Testing a Model to Understand Relationships between e-Learning Outcomes and Human Factors (SBE, NJA), pp. 361–370.
ICEISICEIS-v2-2013-KalsingITN #incremental #learning #legacy #mining #modelling #process #using
Evolutionary Learning of Business Process Models from Legacy Systems using Incremental Process Mining (ACK, CI, LHT, GSdN), pp. 58–69.
ICEISICEIS-v2-2013-LiL #agile #network #object-oriented #predict #process #using
Predicting Fault-proneness of Object-Oriented System Developed with Agile Process using Learned Bayesian Network (LL, HL), pp. 5–16.
ICEISICEIS-v2-2013-MoreiraF #learning #mobile
A Blended Mobile Learning Context Oriented Model in a Cloud Environment applied to a RE Course (FM, MJF), pp. 539–544.
ICEISICEIS-v2-2013-SantaN #framework #learning #modelling #using
Modeling the Creation of a Learning Organization by using the Learning Organization Atlas Framework (MS, SN), pp. 278–285.
ICEISICEIS-v3-2013-VielMPT #how #interactive #learning #multi #student
How are they Watching Me — Learning from Student Interactions with Multimedia Objects Captured from Classroom Presentations (CCV, ELM, MdGCP, CACT), pp. 5–16.
CIKMCIKM-2013-BaragliaMNS #learning #named #predict
LearNext: learning to predict tourists movements (RB, CIM, FMN, FS), pp. 751–756.
CIKMCIKM-2013-CeccarelliLOPT #learning #metric
Learning relatedness measures for entity linking (DC, CL, SO, RP, ST), pp. 139–148.
CIKMCIKM-2013-ChengCLWAC #data type #learning #multi
Feedback-driven multiclass active learning for data streams (YC, ZC, LL, JW, AA, ANC), pp. 1311–1320.
CIKMCIKM-2013-ChenW #classification #learning #scalability
Cost-sensitive learning for large-scale hierarchical classification (JC, DW), pp. 1351–1360.
CIKMCIKM-2013-FangZ #feature model #learning #multi
Discriminative feature selection for multi-view cross-domain learning (ZF, Z(Z), pp. 1321–1330.
CIKMCIKM-2013-Guestrin #machine learning #scalability #usability
Usability in machine learning at scale with graphlab (CG), pp. 5–6.
CIKMCIKM-2013-HashemiNB #approach #learning #network #retrieval #topic
Expertise retrieval in bibliographic network: a topic dominance learning approach (SHH, MN, HB), pp. 1117–1126.
CIKMCIKM-2013-KamathC #learning #predict #what
Spatio-temporal meme prediction: learning what hashtags will be popular where (KYK, JC), pp. 1341–1350.
ECIRECIR-2013-DangBC #information retrieval #learning #rank
Two-Stage Learning to Rank for Information Retrieval (VD, MB, WBC), pp. 423–434.
ECIRECIR-2013-JuMJ #classification #learning #rank
Learning to Rank from Structures in Hierarchical Text Classification (QJ, AM, RJ), pp. 183–194.
ECIRECIR-2013-NguyenTT #classification #learning #rank #using
Folktale Classification Using Learning to Rank (DN, DT, MT), pp. 195–206.
ICMLICML-c1-2013-0005LSL #feature model #learning #modelling #online
Online Feature Selection for Model-based Reinforcement Learning (TTN, ZL, TS, TYL), pp. 498–506.
ICMLICML-c1-2013-AbernethyAKD #learning #problem #scalability
Large-Scale Bandit Problems and KWIK Learning (JA, KA, MK, MD), pp. 588–596.
ICMLICML-c1-2013-AfkanpourGSB #algorithm #kernel #learning #multi #random #scalability
A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning (AA, AG, CS, MB), pp. 374–382.
ICMLICML-c1-2013-AnandkumarHJK #learning #linear #network
Learning Linear Bayesian Networks with Latent Variables (AA, DH, AJ, SK), pp. 249–257.
ICMLICML-c1-2013-BalcanBEL #learning #performance
Efficient Semi-supervised and Active Learning of Disjunctions (NB, CB, SE, YL), pp. 633–641.
ICMLICML-c1-2013-BootsG #approach #learning
A Spectral Learning Approach to Range-Only SLAM (BB, GJG), pp. 19–26.
ICMLICML-c1-2013-ChenK #adaptation #learning #optimisation
Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization (YC, AK), pp. 160–168.
ICMLICML-c1-2013-CotterSS #learning
Learning Optimally Sparse Support Vector Machines (AC, SSS, NS), pp. 266–274.
ICMLICML-c1-2013-GiguereLMS #algorithm #approach #bound #learning #predict
Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction (SG, FL, MM, KS), pp. 107–114.
ICMLICML-c1-2013-GolubCY #learning
Learning an Internal Dynamics Model from Control Demonstration (MG, SC, BY), pp. 606–614.
ICMLICML-c1-2013-GonenSS #approach #learning #performance
Efficient Active Learning of Halfspaces: an Aggressive Approach (AG, SS, SSS), pp. 480–488.
ICMLICML-c1-2013-GongGS #adaptation #invariant #learning
Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation (BG, KG, FS), pp. 222–230.
ICMLICML-c1-2013-KadriGP #approach #kernel #learning
A Generalized Kernel Approach to Structured Output Learning (HK, MG, PP), pp. 471–479.
ICMLICML-c1-2013-KarbasiSS #learning
Iterative Learning and Denoising in Convolutional Neural Associative Memories (AK, AHS, AS), pp. 445–453.
ICMLICML-c1-2013-KumarB #bound #graph #learning
Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs (KSSK, FRB), pp. 525–533.
ICMLICML-c1-2013-LiLSHD #generative #learning #using
Learning Hash Functions Using Column Generation (XL, GL, CS, AvdH, ARD), pp. 142–150.
ICMLICML-c1-2013-LimLM #learning #metric #robust
Robust Structural Metric Learning (DL, GRGL, BM), pp. 615–623.
ICMLICML-c1-2013-MaatenCTW #learning
Learning with Marginalized Corrupted Features (LvdM, MC, ST, KQW), pp. 410–418.
ICMLICML-c1-2013-MaillardNOR #bound #learning #representation
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning (OAM, PN, RO, DR), pp. 543–551.
ICMLICML-c1-2013-MenonTGLK #framework #machine learning #programming
A Machine Learning Framework for Programming by Example (AKM, OT, SG, BWL, AK), pp. 187–195.
ICMLICML-c1-2013-RuvoloE #algorithm #learning #named #performance
ELLA: An Efficient Lifelong Learning Algorithm (PR, EE), pp. 507–515.
ICMLICML-c1-2013-ZuluagaSKP #learning #multi #optimisation
Active Learning for Multi-Objective Optimization (MZ, GS, AK, MP), pp. 462–470.
ICMLICML-c2-2013-GaneshapillaiGL #learning
Learning Connections in Financial Time Series (GG, JVG, AL), pp. 109–117.
ICMLICML-c2-2013-GolovinSMY #learning #ram #scalability
Large-Scale Learning with Less RAM via Randomization (DG, DS, HBM, MY), pp. 325–333.
ICMLICML-c2-2013-KrummenacherOB #learning #multi
Ellipsoidal Multiple Instance Learning (GK, CSO, JMB), pp. 73–81.
ICMLICML-c2-2013-MaurerPR #learning #multi
Sparse coding for multitask and transfer learning (AM, MP, BRP), pp. 343–351.
ICMLICML-c2-2013-MeentBWGW #learning #markov #modelling
Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data (JWvdM, JEB, FW, RLG, CW), pp. 361–369.
ICMLICML-c2-2013-MinhBM #framework #learning #multi
A unifying framework for vector-valued manifold regularization and multi-view learning (HQM, LB, VM), pp. 100–108.
ICMLICML-c2-2013-RanganathWBX #adaptation #learning #probability
An Adaptive Learning Rate for Stochastic Variational Inference (RR, CW, DMB, EPX), pp. 298–306.
ICMLICML-c2-2013-SohnZLL #learning
Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines (KS, GZ, CL, HL), pp. 217–225.
ICMLICML-c2-2013-Tran-DinhKC #framework #graph #learning #matrix
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions (QTD, ATK, VC), pp. 271–279.
ICMLICML-c2-2013-TranPV #learning #multi
Thurstonian Boltzmann Machines: Learning from Multiple Inequalities (TT, DQP, SV), pp. 46–54.
ICMLICML-c2-2013-YangH #classification #learning
Activized Learning with Uniform Classification Noise (LY, SH), pp. 370–378.
ICMLICML-c3-2013-0002T #kernel #learning
Differentially Private Learning with Kernels (PJ, AT), pp. 118–126.
ICMLICML-c3-2013-AlmingolML #behaviour #learning #multi
Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space (JA, LM, ML), pp. 136–144.
ICMLICML-c3-2013-BalasubramanianYL #learning
Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations (KB, KY, GL), pp. 289–297.
ICMLICML-c3-2013-BalcanBM #learning #ontology
Exploiting Ontology Structures and Unlabeled Data for Learning (NB, AB, YM), pp. 1112–1120.
ICMLICML-c3-2013-BellemareVB #learning #recursion
Bayesian Learning of Recursively Factored Environments (MGB, JV, MB), pp. 1211–1219.
ICMLICML-c3-2013-BrechtelGD #incremental #learning #performance #representation
Solving Continuous POMDPs: Value Iteration with Incremental Learning of an Efficient Space Representation (SB, TG, RD), pp. 370–378.
ICMLICML-c3-2013-ChattopadhyayFDPY #learning
Joint Transfer and Batch-mode Active Learning (RC, WF, ID, SP, JY), pp. 253–261.
ICMLICML-c3-2013-Cheng #learning #similarity
Riemannian Similarity Learning (LC), pp. 540–548.
ICMLICML-c3-2013-CoatesHWWCN #learning #off the shelf
Deep learning with COTS HPC systems (AC, BH, TW, DJW, BCC, AYN), pp. 1337–1345.
ICMLICML-c3-2013-DalalyanHMS #learning #modelling #programming
Learning Heteroscedastic Models by Convex Programming under Group Sparsity (ASD, MH, KM, JS), pp. 379–387.
ICMLICML-c3-2013-DimitrakakisT #learning
ABC Reinforcement Learning (CD, NT), pp. 684–692.
ICMLICML-c3-2013-GensD #learning #network
Learning the Structure of Sum-Product Networks (RG, PMD), pp. 873–880.
ICMLICML-c3-2013-GittensM #machine learning #scalability
Revisiting the Nystrom method for improved large-scale machine learning (AG, MWM), pp. 567–575.
ICMLICML-c3-2013-GuptaPV #approach #learning #multi #parametricity
Factorial Multi-Task Learning : A Bayesian Nonparametric Approach (SKG, DQP, SV), pp. 657–665.
ICMLICML-c3-2013-HockingRVB #detection #learning #using
Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression (TH, GR, JPV, FRB), pp. 172–180.
ICMLICML-c3-2013-HoXV #learning #on the #taxonomy
On A Nonlinear Generalization of Sparse Coding and Dictionary Learning (JH, YX, BCV), pp. 1480–1488.
ICMLICML-c3-2013-HuangS #learning #markov #modelling
Spectral Learning of Hidden Markov Models from Dynamic and Static Data (TKH, JGS), pp. 630–638.
ICMLICML-c3-2013-JancsaryNR #learning #predict
Learning Convex QP Relaxations for Structured Prediction (JJ, SN, CR), pp. 915–923.
ICMLICML-c3-2013-JoseGAV #kernel #learning #performance #predict
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction (CJ, PG, PA, MV), pp. 486–494.
ICMLICML-c3-2013-JoulaniGS #feedback #learning #online
Online Learning under Delayed Feedback (PJ, AG, CS), pp. 1453–1461.
ICMLICML-c3-2013-JunZSR #learning
Learning from Human-Generated Lists (KSJ, X(Z, BS, TTR), pp. 181–189.
ICMLICML-c3-2013-KarS0K #algorithm #learning #on the #online
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions (PK, BKS, PJ, HK), pp. 441–449.
ICMLICML-c3-2013-KontorovichNW #learning #on the
On learning parametric-output HMMs (AK, BN, RW), pp. 702–710.
ICMLICML-c3-2013-KoppulaS #detection #learning #process
Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and Anticipation (HSK, AS), pp. 792–800.
ICMLICML-c3-2013-KraehenbuehlK #convergence #learning #parametricity #random
Parameter Learning and Convergent Inference for Dense Random Fields (PK, VK), pp. 513–521.
ICMLICML-c3-2013-KuzborskijO #learning
Stability and Hypothesis Transfer Learning (IK, FO), pp. 942–950.
ICMLICML-c3-2013-LattimoreHS #learning
The Sample-Complexity of General Reinforcement Learning (TL, MH, PS), pp. 28–36.
ICMLICML-c3-2013-MalioutovV #learning
Exact Rule Learning via Boolean Compressed Sensing (DMM, KRV), pp. 765–773.
ICMLICML-c3-2013-MemisevicE #invariant #learning #problem
Learning invariant features by harnessing the aperture problem (RM, GE), pp. 100–108.
ICMLICML-c3-2013-NiuJDHS #approach #learning #novel
Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning (GN, WJ, BD, HH, MS), pp. 10–18.
ICMLICML-c3-2013-RamanJSS #learning
Stable Coactive Learning via Perturbation (KR, TJ, PS, TS), pp. 837–845.
ICMLICML-c3-2013-Romera-ParedesABP #learning #multi
Multilinear Multitask Learning (BRP, HA, NBB, MP), pp. 1444–1452.
ICMLICML-c3-2013-RossZYDB #learning #policy #predict
Learning Policies for Contextual Submodular Prediction (SR, JZ, YY, DD, DB), pp. 1364–1372.
ICMLICML-c3-2013-SchaulZL #learning
No more pesky learning rates (TS, SZ, YL), pp. 343–351.
ICMLICML-c3-2013-SilverNBWM #concurrent #interactive #learning
Concurrent Reinforcement Learning from Customer Interactions (DS, LN, DB, SW, JM), pp. 924–932.
ICMLICML-c3-2013-SimsekliCY #learning #matrix #modelling
Learning the β-Divergence in Tweedie Compound Poisson Matrix Factorization Models (US, ATC, YKY), pp. 1409–1417.
ICMLICML-c3-2013-SodomkaHLG #game studies #learning #named #probability
Coco-Q: Learning in Stochastic Games with Side Payments (ES, EH, MLL, AG), pp. 1471–1479.
ICMLICML-c3-2013-SutskeverMDH #learning #on the
On the importance of initialization and momentum in deep learning (IS, JM, GED, GEH), pp. 1139–1147.
ICMLICML-c3-2013-TarlowSCSZ #learning #probability
Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning (DT, KS, LC, IS, RSZ), pp. 199–207.
ICMLICML-c3-2013-WangNH #learning #robust #self
Robust and Discriminative Self-Taught Learning (HW, FN, HH), pp. 298–306.
ICMLICML-c3-2013-WangNH13a #clustering #learning #multi
Multi-View Clustering and Feature Learning via Structured Sparsity (HW, FN, HH), pp. 352–360.
ICMLICML-c3-2013-WangWBLT #learning #multi #taxonomy
Max-Margin Multiple-Instance Dictionary Learning (XW, BW, XB, WL, ZT), pp. 846–854.
ICMLICML-c3-2013-XuKHW #learning #representation
Anytime Representation Learning (ZEX, MJK, GH, KQW), pp. 1076–1084.
ICMLICML-c3-2013-YangLZ #learning #matrix #multi
Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model (MY, YL, ZZ), pp. 423–431.
ICMLICML-c3-2013-YuLKJC #learning
∝SVM for Learning with Label Proportions (FXY, DL, SK, TJ, SFC), pp. 504–512.
ICMLICML-c3-2013-ZemelWSPD #learning
Learning Fair Representations (RSZ, YW, KS, TP, CD), pp. 325–333.
ICMLICML-c3-2013-ZhangYJLH #bound #kernel #learning #online
Online Kernel Learning with a Near Optimal Sparsity Bound (LZ, JY, RJ, ML, XH), pp. 621–629.
ICMLICML-c3-2013-ZhouZS #kernel #learning #multi #process
Learning Triggering Kernels for Multi-dimensional Hawkes Processes (KZ, HZ, LS), pp. 1301–1309.
ICMLICML-c3-2013-ZweigW #learning
Hierarchical Regularization Cascade for Joint Learning (AZ, DW), pp. 37–45.
KDDKDD-2013-BahadoriLX #learning #performance #probability #process
Fast structure learning in generalized stochastic processes with latent factors (MTB, YL, EPX), pp. 284–292.
KDDKDD-2013-ChakrabartiH #learning #scalability #social
Speeding up large-scale learning with a social prior (DC, RH), pp. 650–658.
KDDKDD-2013-ChenHKB #learning #named
DTW-D: time series semi-supervised learning from a single example (YC, BH, EJK, GEAPAB), pp. 383–391.
KDDKDD-2013-DasMGW #learning
Learning to question: leveraging user preferences for shopping advice (MD, GDFM, AG, IW), pp. 203–211.
KDDKDD-2013-FeiKSNMH #detection #learning
Heat pump detection from coarse grained smart meter data with positive and unlabeled learning (HF, YK, SS, MRN, SKM, JH), pp. 1330–1338.
KDDKDD-2013-GeGLZ #estimation #learning #multi
Multi-source deep learning for information trustworthiness estimation (LG, JG, XL, AZ), pp. 766–774.
KDDKDD-2013-GilpinED #algorithm #framework #learning
Guided learning for role discovery (GLRD): framework, algorithms, and applications (SG, TER, IND), pp. 113–121.
KDDKDD-2013-HaoCZ0RK #learning #towards
Towards never-ending learning from time series streams (YH, YC, JZ, BH, TR, EJK), pp. 874–882.
KDDKDD-2013-Howard #learning
The business impact of deep learning (JH), p. 1135.
KDDKDD-2013-KongY #automation #classification #distance #learning
Discriminant malware distance learning on structural information for automated malware classification (DK, GY), pp. 1357–1365.
KDDKDD-2013-KutzkovBBG #learning #named
STRIP: stream learning of influence probabilities (KK, AB, FB, AG), pp. 275–283.
KDDKDD-2013-LinWHY #information management #learning #modelling #social
Extracting social events for learning better information diffusion models (SL, FW, QH, PSY), pp. 365–373.
KDDKDD-2013-LiuFYX #learning #recommendation
Learning geographical preferences for point-of-interest recommendation (BL, YF, ZY, HX), pp. 1043–1051.
KDDKDD-2013-MorenoNK #graph #learning #modelling
Learning mixed kronecker product graph models with simulated method of moments (SM, JN, SK), pp. 1052–1060.
KDDKDD-2013-SutherlandPS #learning #matrix #rank
Active learning and search on low-rank matrices (DJS, BP, JGS), pp. 212–220.
KDDKDD-2013-TanXGW #learning #metric #modelling #optimisation #rank #ranking
Direct optimization of ranking measures for learning to rank models (MT, TX, LG, SW), pp. 856–864.
KDDKDD-2013-Vatsavai #approach #learning #multi #using
Gaussian multiple instance learning approach for mapping the slums of the world using very high resolution imagery (RRV), pp. 1419–1426.
KDDKDD-2013-WangY #learning #query
Querying discriminative and representative samples for batch mode active learning (ZW, JY), pp. 158–166.
KDDKDD-2013-Wright #data analysis #learning #optimisation
Optimization in learning and data analysis (SJW), p. 3.
KDDKDD-2013-XiangYFWTY #learning #multi #predict
Multi-source learning with block-wise missing data for Alzheimer’s disease prediction (SX, LY, WF, YW, PMT, JY), pp. 185–193.
KDDKDD-2013-ZhangHL #learning #multi #named
MI2LS: multi-instance learning from multiple informationsources (DZ, JH, RDL), pp. 149–157.
KDDKDD-2013-ZhaoH #detection #learning #online
Cost-sensitive online active learning with application to malicious URL detection (PZ, SCHH), pp. 919–927.
KDDKDD-2013-ZhaoYNG #framework #learning #twitter
A transfer learning based framework of crowd-selection on twitter (ZZ, DY, WN, SG), pp. 1514–1517.
KDIRKDIR-KMIS-2013-AtrashAM #enterprise #learning #semantics
A Semantic Model for Small and Medium-sized Enterprises to Support Organizational Learning (AA, MHA, CM), pp. 476–483.
KDIRKDIR-KMIS-2013-BerkaniN #collaboration #learning #recommendation #semantics
Semantic Collaborative Filtering for Learning Objects Recommendation (LB, ON), pp. 52–63.
KDIRKDIR-KMIS-2013-CastellanoS
Developing Innovative e-Learning Solutions (MC, FAS), pp. 484–489.
KDIRKDIR-KMIS-2013-Dessne #learning
Learning in an Organisation — Exploring the Nature of Relationships (KD), pp. 496–501.
KDIRKDIR-KMIS-2013-Eardley #information management #learning
Negotiated Work-based Learning and Organisational Learning — The Relationship between Individual and Organisational Knowledge Management (AE), pp. 1–5.
KDIRKDIR-KMIS-2013-NhungNCLT #approach #image #learning #multi
A Multiple Instance Learning Approach to Image Annotation with Saliency Map (TPN, CTN, JC, HVL, TT), pp. 152–159.
KDIRKDIR-KMIS-2013-SaxenaBW #composition #learning
A Cognitive Reference based Model for Learning Compositional Hierarchies with Whole-composite Tags (ABS, AB, AW), pp. 119–127.
KEODKEOD-2013-WohlgenanntBS #automation #evolution #learning #ontology #prototype
A Prototype for Automating Ontology Learning and Ontology Evolution (GW, SB, MS), pp. 407–412.
MLDMMLDM-2013-BouillonAA #evolution #fuzzy #gesture #learning #recognition
Decremental Learning of Evolving Fuzzy Inference Systems: Application to Handwritten Gesture Recognition (MB, ÉA, AA), pp. 115–129.
MLDMMLDM-2013-ElGibreenA #learning #multi #product line
Multi Model Transfer Learning with RULES Family (HE, MSA), pp. 42–56.
MLDMMLDM-2013-GopalakrishnaOLL #algorithm #machine learning #metric
Relevance as a Metric for Evaluating Machine Learning Algorithms (AKG, TO, AL, JJL), pp. 195–208.
MLDMMLDM-2013-KoharaS #learning #self
Typhoon Damage Scale Forecasting with Self-Organizing Maps Trained by Selective Presentation Learning (KK, IS), pp. 16–26.
MLDMMLDM-2013-MaziluCGRHT #detection #learning #predict
Feature Learning for Detection and Prediction of Freezing of Gait in Parkinson’s Disease (SM, AC, EG, DR, JMH, GT), pp. 144–158.
MLDMMLDM-2013-Suthaharan #big data #classification #network
A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion (SS), pp. 296–310.
RecSysRecSys-2013-HuY #learning #process #recommendation
Interview process learning for top-n recommendation (FH, YY), pp. 331–334.
RecSysRecSys-2013-KaratzoglouBS #learning #rank #recommendation
Learning to rank for recommender systems (AK, LB, YS), pp. 493–494.
RecSysRecSys-2013-KucharK #case study #learning #named #web #web service
GAIN: web service for user tracking and preference learning — a smart TV use case (JK, TK), pp. 467–468.
RecSysRecSys-2013-SharmaY #community #learning #recommendation
Pairwise learning in recommendation: experiments with community recommendation on linkedin (AS, BY), pp. 193–200.
RecSysRecSys-2013-WestonYW #learning #rank #recommendation #statistics
Learning to rank recommendations with the k-order statistic loss (JW, HY, RJW), pp. 245–248.
SEKESEKE-2013-BarbosaFNM #architecture #learning #towards
Towards the Establishment of a Reference Architecture for Developing Learning Environments (EFB, MLF, EYN, JCM), pp. 350–355.
SEKESEKE-2013-CarrerasZO #machine learning
A Machine Learning Based File Archival Tool (S) (RC, DZ, JO), pp. 73–76.
SEKESEKE-2013-HoritaHGB #development #maturity #quality
Maturity Model and Lesson Learned for improve the Quality of Organizational Knowledge and Human Resources Management in Software Development (S) (FEAH, MIH, FHG, RMdB), pp. 552–555.
SIGIRSIGIR-2013-DalipGCC #case study #feedback #rank #stack overflow
Exploiting user feedback to learn to rank answers in q&a forums: a case study with stack overflow (DHD, MAG, MC, PC), pp. 543–552.
SIGIRSIGIR-2013-LimsopathamMO #learning
Learning to combine representations for medical records search (NL, CM, IO), pp. 833–836.
SIGIRSIGIR-2013-Moschitti #kernel #learning #rank #semantics
Kernel-based learning to rank with syntactic and semantic structures (AM), p. 1128.
SIGIRSIGIR-2013-Shokouhi #learning #personalisation #query
Learning to personalize query auto-completion (MS), pp. 103–112.
SIGIRSIGIR-2013-WangHWZ0M #learning #multimodal #search-based
Learning to name faces: a multimodal learning scheme for search-based face annotation (DW, SCHH, PW, JZ, YH, CM), pp. 443–452.
SIGIRSIGIR-2013-ZhangWYW #learning #network #predict
Learning latent friendship propagation networks with interest awareness for link prediction (JZ, CW, PSY, JW), pp. 63–72.
ICMTICMT-2013-FaunesSB #approach #model transformation
Genetic-Programming Approach to Learn Model Transformation Rules from Examples (MF, HAS, MB), pp. 17–32.
OOPSLAOOPSLA-2013-ChoiNS #android #approximate #learning #testing #user interface
Guided GUI testing of android apps with minimal restart and approximate learning (WC, GCN, KS), pp. 623–640.
POPLPOPL-2013-BotincanB #learning #specification
Sigma*: symbolic learning of input-output specifications (MB, DB), pp. 443–456.
POPLPOPL-2013-DSilvaHK #learning
Abstract conflict driven learning (VD, LH, DK), pp. 143–154.
RERE-2013-ShiWL #evolution #learning #predict
Learning from evolution history to predict future requirement changes (LS, QW, ML), pp. 135–144.
RERE-2013-SultanovH #learning #requirements
Application of reinforcement learning to requirements engineering: requirements tracing (HS, JHH), pp. 52–61.
REFSQREFSQ-2013-TjongB #ambiguity #design #lessons learnt #prototype #requirements #specification
The Design of SREE — A Prototype Potential Ambiguity Finder for Requirements Specifications and Lessons Learned (SFT, DMB), pp. 80–95.
SACSAC-2013-AkritidisB #algorithm #classification #machine learning #research
A supervised machine learning classification algorithm for research articles (LA, PB), pp. 115–120.
SACSAC-2013-BerralGT #automation #machine learning
Empowering automatic data-center management with machine learning (JLB, RG, JT), pp. 170–172.
SACSAC-2013-BlondelSU #classification #constraints #learning #using
Learning non-linear classifiers with a sparsity constraint using L1 regularization (MB, KS, KU), pp. 167–169.
SACSAC-2013-FilhoB #learning #mobile #requirements
A requirements catalog for mobile learning environments (NFDF, EFB), pp. 1266–1271.
SACSAC-2013-LinCLG #approach #data-driven #distributed #learning #predict
Distributed dynamic data driven prediction based on reinforcement learning approach (SYL, KMC, CCL, NG), pp. 779–784.
SACSAC-2013-LommatzschKA #hybrid #learning #modelling #recommendation #semantics
Learning hybrid recommender models for heterogeneous semantic data (AL, BK, SA), pp. 275–276.
SACSAC-2013-SeelandKP #graph #kernel #learning
Model selection based product kernel learning for regression on graphs (MS, SK, BP), pp. 136–143.
SACSAC-2013-SinghR #algorithm #architecture #optimisation #predict
Meta-learning based architectural and algorithmic optimization for achieving green-ness in predictive workload analytics (NS, SR), pp. 1169–1176.
ICSEICSE-2013-CotroneoPR #testing
A learning-based method for combining testing techniques (DC, RP, SR), pp. 142–151.
ICSEICSE-2013-Jonsson #machine learning #performance #scalability #using
Increasing anomaly handling efficiency in large organizations using applied machine learning (LJ), pp. 1361–1364.
ICSEICSE-2013-KimNSK #automation #generative
Automatic patch generation learned from human-written patches (DK, JN, JS, SK), pp. 802–811.
ICSEICSE-2013-MengKM #learning #named
LASE: locating and applying systematic edits by learning from examples (NM, MK, KSM), pp. 502–511.
ICSEICSE-2013-NamPK #fault #learning
Transfer defect learning (JN, SJP, SK), pp. 382–391.
ICSEICSE-2013-SykesCMKRI #adaptation #learning #modelling
Learning revised models for planning in adaptive systems (DS, DC, JM, JK, AR, KI), pp. 63–71.
ICSEICSE-2013-TillmannHXGB #education #game studies #interactive #learning #programming #re-engineering
Teaching and learning programming and software engineering via interactive gaming (NT, JdH, TX, SG, JB), pp. 1117–1126.
CCCC-2013-MooreC #automation #generative #machine learning #policy #using
Automatic Generation of Program Affinity Policies Using Machine Learning (RWM, BRC), pp. 184–203.
CGOCGO-2013-KulkarniCWS #automation #heuristic #machine learning #using
Automatic construction of inlining heuristics using machine learning (SK, JC, CW, DS), p. 12.
CAVCAV-2013-0001LMN #data type #invariant #learning #linear #quantifier
Learning Universally Quantified Invariants of Linear Data Structures (PG, CL, PM, DN), pp. 813–829.
CAVCAV-2013-ChagantyLNR #learning #relational #smt #using
Combining Relational Learning with SMT Solvers Using CEGAR (ATC, AL, AVN, SKR), pp. 447–462.
ICSTICST-2013-BotellaBCLLS #component #encryption #experience #lessons learnt #modelling #testing
Model-Based Testing of Cryptographic Components — Lessons Learned from Experience (JB, FB, JFC, FL, BL, FS), pp. 192–201.
ICSTICST-2013-MeinkeS #named #testing
LBTest: A Learning-Based Testing Tool for Reactive Systems (KM, MAS), pp. 447–454.
ICTSSICTSS-2013-FengLMNSW #case study #testing
Case Studies in Learning-Based Testing (LF, SL, KM, FN, MAS, PYHW), pp. 164–179.
ISSTAISSTA-2013-HowarGR #analysis #generative #hybrid #interface #learning
Hybrid learning: interface generation through static, dynamic, and symbolic analysis (FH, DG, ZR), pp. 268–279.
ISSTAISSTA-2013-TrippWG #approach #learning #security #testing #web
Finding your way in the testing jungle: a learning approach to web security testing (OT, OW, LG), pp. 347–357.
ICSTSAT-2013-Ben-Ari #education #named #satisfiability
LearnSAT: A SAT Solver for Education (MBA), pp. 403–407.
ICSTSAT-2013-Johannsen #exponential #learning #proving
Exponential Separations in a Hierarchy of Clause Learning Proof Systems (JJ), pp. 40–51.
ICSTSAT-2013-LonsingEG #learning #performance #pseudo #quantifier
Efficient Clause Learning for Quantified Boolean Formulas via QBF Pseudo Unit Propagation (FL, UE, AVG), pp. 100–115.
CBSECBSE-2012-AbateCTZ #component #future of #learning #repository
Learning from the future of component repositories (PA, RDC, RT, SZ), pp. 51–60.
ASEASE-2012-LuCC #fault #learning #predict #reduction #using
Software defect prediction using semi-supervised learning with dimension reduction (HL, BC, MC), pp. 314–317.
CASECASE-2012-AnKP #learning #modelling #process
Grasp motion learning with Gaussian Process Dynamic Models (BA, HK, FCP), pp. 1114–1119.
CASECASE-2012-YamamotoD #interface #learning
Robot interface learning user-defined voice instructions (DY, MD), pp. 926–929.
DACDAC-2012-WardDP #automation #evaluation #learning #named
PADE: a high-performance placer with automatic datapath extraction and evaluation through high dimensional data learning (SIW, DD, DZP), pp. 756–761.
DATEDATE-2012-MaricauJG #analysis #learning #multi #reliability #using
Hierarchical analog circuit reliability analysis using multivariate nonlinear regression and active learning sample selection (EM, DdJ, GGEG), pp. 745–750.
DocEngDocEng-2012-MoulderM #how #layout #learning
Learning how to trade off aesthetic criteria in layout (PM, KM), pp. 33–36.
HTHT-2012-SchofeggerKSG #behaviour #learning #social
Learning user characteristics from social tagging behavior (KS, CK, PS, MG), pp. 207–212.
SIGMODSIGMOD-2012-AbiteboulAMS #learning #xml
Auto-completion learning for XML (SA, YA, TM, PS), pp. 669–672.
SIGMODSIGMOD-2012-LinK #machine learning #scalability #twitter
Large-scale machine learning at twitter (JL, AK), pp. 793–804.
VLDBVLDB-2012-IseleB #learning #programming #search-based #using
Learning Expressive Linkage Rules using Genetic Programming (RI, CB), pp. 1638–1649.
VLDBVLDB-2012-KanagalAPJYP #behaviour #learning #recommendation #taxonomy #using
Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior (BK, AA, SP, VJ, JY, LGP), pp. 956–967.
VLDBVLDB-2012-LowGKBGH #distributed #framework #in the cloud #machine learning
Distributed GraphLab: A Framework for Machine Learning in the Cloud (YL, JG, AK, DB, CG, JMH), pp. 716–727.
VLDBVLDB-2012-SinghG #learning #semantics #string
Learning Semantic String Transformations from Examples (RS, SG), pp. 740–751.
CSEETCSEET-2012-AroraG #collaboration #learning #programming #source code
Learning to Write Programs with Others: Collaborative Quadruple Programming (RA, SG), pp. 32–41.
CSEETCSEET-2012-BareissS
A Gentle Introduction to Learn by Doing (RB, TS), pp. 81–84.
CSEETCSEET-2012-TillmannHXB #education #game studies #learning #named #social
Pex4Fun: Teaching and Learning Computer Science via Social Gaming (NT, JdH, TX, JB), pp. 90–91.
ITiCSEITiCSE-2012-AsadB #aspect-oriented #concept #image #learning
Are children capable of learning image processing concepts?: cognitive and affective aspects (KA, MB), pp. 227–231.
ITiCSEITiCSE-2012-BaghdadiAR #case study #distance #learning #safety #tool support
Applying advanced technology tools in distance learning: case study: traffic data and road safety (MB, KA, JR), p. 389.
ITiCSEITiCSE-2012-BoyceCPCB #behaviour #game studies #learning
Maximizing learning and guiding behavior in free play user generated content environments (AKB, AC, SP, DC, TB), pp. 10–15.
ITiCSEITiCSE-2012-CamaraPV #collaboration #evaluation #framework #learning #programming
Evaluation of a collaborative instructional framework for programming learning (LMSC, MPV, JÁVI), pp. 162–167.
ITiCSEITiCSE-2012-ChristensenC #learning
Lectures abandoned: active learning by active seminars (HBC, AVC), pp. 16–21.
ITiCSEITiCSE-2012-GomesSM #behaviour #case study #learning #student #towards
A study on students’ behaviours and attitudes towards learning to program (AJG, ÁNS, AJM), pp. 132–137.
ITiCSEITiCSE-2012-GovenderG #learning #object-oriented #programming #student
Are students learning object oriented programming in an object oriented programming course?: student voices (DWG, IG), p. 395.
ITiCSEITiCSE-2012-HamadaN #learning
A learning tool for MP3 audio compression (MH, HN), p. 397.
ITiCSEITiCSE-2012-HiltonJ #array #education #learning #on the #testing
On teaching arrays with test-driven learning in WebIDE (MH, DSJ), pp. 93–98.
ITiCSEITiCSE-2012-KrausePR #learning
Formal learning groups in an introductory CS course: a qualitative exploration (JK, IP, CR), pp. 315–320.
ITiCSEITiCSE-2012-Larraza-MendiluzeGMMRALS
Nintendo® DS projects to learn computer input-output (ELM, NGV, JIM, JM, TRV, ISA, JFL, KS), p. 373.
ITiCSEITiCSE-2012-Luxton-ReillyDPS #how #learning #process #student
Activities, affordances and attitude: how student-generated questions assist learning (ALR, PD, BP, RS), pp. 4–9.
ITiCSEITiCSE-2012-MalekoHD #case study #experience #learning #mobile #programming #social
Novices’ perceptions and experiences of a mobile social learning environment for learning of programming (MM, MH, DJD), pp. 285–290.
ITiCSEITiCSE-2012-MehtaKP #algorithm #learning #network
Forming project groups while learning about matching and network flows in algorithms (DPM, TMK, IP), pp. 40–45.
ITiCSEITiCSE-2012-MeyerW #lessons learnt #programming
Programming studio: advances and lessons learned (CM, MW), p. 369.
ITiCSEITiCSE-2012-MussaiL #animation #concept #learning #object-oriented
An animation as an illustrate tool for learning concepts in oop (YM, NL), p. 386.
ITiCSEITiCSE-2012-MyllymakiH #case study #learning
Choosing a study mode in blended learning (MM, IH), pp. 291–296.
ITiCSEITiCSE-2012-SperlingL #machine learning #re-engineering #student
Integrating AI and machine learning in software engineering course for high school students (AS, DL), pp. 244–249.
ITiCSEITiCSE-2012-Sudol-DeLyserSC #comprehension #learning #problem
Code comprehension problems as learning events (LASD, MS, SC), pp. 81–86.
ITiCSEITiCSE-2012-Velazquez-Iturbide #algorithm #approach #learning #refinement
Refinement of an experimental approach tocomputer-based, active learning of greedy algorithms (JÁVI), pp. 46–51.
FASEFASE-2012-AlrajehKRU #learning #satisfiability #specification
Learning from Vacuously Satisfiable Scenario-Based Specifications (DA, JK, AR, SU), pp. 377–393.
TACASTACAS-2012-DSilvaHKT #analysis #bound #learning
Numeric Bounds Analysis with Conflict-Driven Learning (VD, LH, DK, MT), pp. 48–63.
TACASTACAS-2012-MertenHSCJ #automaton #learning
Demonstrating Learning of Register Automata (MM, FH, BS, SC, BJ), pp. 466–471.
ICPCICPC-2012-Sajnani #approach #architecture #automation #machine learning
Automatic software architecture recovery: A machine learning approach (HS), pp. 265–268.
ICSMEICSM-2012-BoomsmaHG #industrial #lessons learnt #php #web
Dead code elimination for web systems written in PHP: Lessons learned from an industry case (HB, BVH, HGG), pp. 511–515.
SASSAS-2012-GiannakopoulouRR #component #interface #learning
Symbolic Learning of Component Interfaces (DG, ZR, VR), pp. 248–264.
STOCSTOC-2012-DaskalakisDS #learning
Learning poisson binomial distributions (CD, ID, RAS), pp. 709–728.
DLTDLT-2012-BoiretLN #learning
Learning Rational Functions (AB, AL, JN), pp. 273–283.
LATALATA-2012-GeilkeZ #algorithm #learning #pattern matching #polynomial
Polynomial-Time Algorithms for Learning Typed Pattern Languages (MG, SZ), pp. 277–288.
LATALATA-2012-Yoshinaka #context-free grammar #integration #learning
Integration of the Dual Approaches in the Distributional Learning of Context-Free Grammars (RY), pp. 538–550.
FMFM-2012-AartsHKOV #abstraction #automaton #learning #refinement
Automata Learning through Counterexample Guided Abstraction Refinement (FA, FH, HK, PO, FWV), pp. 10–27.
CHICHI-2012-AmershiFW #interactive #machine learning #named #network #on-demand #social
Regroup: interactive machine learning for on-demand group creation in social networks (SA, JF, DSW), pp. 21–30.
CHICHI-2012-ChinF #difference #health #learning
Age differences in exploratory learning from a health information website (JC, WTF), pp. 3031–3040.
CHICHI-2012-DongDJKNA #game studies #learning
Discovery-based games for learning software (TD, MD, DJ, KK, MWN, MSA), pp. 2083–2086.
CHICHI-2012-JainB #learning #performance
User learning and performance with bezel menus (MJ, RB), pp. 2221–2230.
CHICHI-2012-OganFMDMC #exclamation #interactive #learning #quote #social
“Oh dear Stacy!”: social interaction, elaboration, and learning with teachable agents (AO, SLF, EM, CD, NM, JC), pp. 39–48.
CHICHI-2012-ParkC12a #adaptation #deployment #design #learning
Adaptation as design: learning from an EMR deployment study (SYP, YC), pp. 2097–2106.
CHICHI-2012-VitakIDEG #learning
Gaze-augmented think-aloud as an aid to learning (SAV, JEI, ATD, SE, AKG), pp. 2991–3000.
CHICHI-2012-XuBRTM #communication #how #learning #towards
Learning how to feel again: towards affective workplace presence and communication technologies (AX, JTB, EGR, TT, WvM), pp. 839–848.
CSCWCSCW-2012-HemphillO #adaptation #bibliography #community #gender #learning
Learning the lingo?: gender, prestige and linguistic adaptation in review communities (LH, JO), pp. 305–314.
CSCWCSCW-2012-LeeTH #coordination #named
Micro-coordination: because we did not already learn everything we need to know about working with others in kindergarten (JSL, DGT, SH), pp. 1135–1144.
CSCWCSCW-2012-RzeszotarskiK #learning #predict #wiki #word
Learning from history: predicting reverted work at the word level in wikipedia (JMR, AK), pp. 437–440.
CSCWCSCW-2012-SarcevicPWSBA #coordination #distributed #learning
“Beacons of hope” in decentralized coordination: learning from on-the-ground medical twitterers during the 2010 Haiti earthquake (AS, LP, JW, KS, MB, KMA), pp. 47–56.
ICEISICEIS-J-2012-RibeiroFBKE #algorithm #approach #learning #markov #process
Combining Learning Algorithms: An Approach to Markov Decision Processes (RR, FF, MACB, ALK, FE), pp. 172–188.
ICEISICEIS-v1-2012-RibeiroFBBDKE #algorithm #approach #learning
Unified Algorithm to Improve Reinforcement Learning in Dynamic Environments — An Instance-based Approach (RR, FF, MACB, APB, OBD, ALK, FE), pp. 229–238.
CIKMCIKM-2012-AgarwalRSMLGF #learning #rank #robust
Learning to rank for robust question answering (AA, HR, KS, PM, RDL, DG, JF), pp. 833–842.
CIKMCIKM-2012-AnHS #learning #ontology #web
Learning to discover complex mappings from web forms to ontologies (YA, XH, IYS), pp. 1253–1262.
CIKMCIKM-2012-CaiZ #injection #learning #rank
Variance maximization via noise injection for active sampling in learning to rank (WC, YZ), pp. 1809–1813.
CIKMCIKM-2012-ChaliHI #learning #performance
Improving the performance of the reinforcement learning model for answering complex questions (YC, SAH, KI), pp. 2499–2502.
CIKMCIKM-2012-ChengZXAC #classification #learning #on the
On active learning in hierarchical classification (YC, KZ, YX, AA, ANC), pp. 2467–2470.
CIKMCIKM-2012-Cohen #learning #metric #random #similarity
Learning similarity measures based on random walks (WWC), p. 3.
CIKMCIKM-2012-CuiMWGL #image #keyword #semantics
Semantically coherent image annotation with a learning-based keyword propagation strategy (CC, JM, SW, SG, TL), pp. 2423–2426.
CIKMCIKM-2012-FangS #approach #feedback #learning #recommendation
A latent pairwise preference learning approach for recommendation from implicit feedback (YF, LS), pp. 2567–2570.
CIKMCIKM-2012-GuoMCJ #learning #recommendation #social
Learning to recommend with social relation ensemble (LG, JM, ZC, HJ), pp. 2599–2602.
CIKMCIKM-2012-KanhabuaN #learning #query #rank
Learning to rank search results for time-sensitive queries (NK, KN), pp. 2463–2466.
CIKMCIKM-2012-LiBCH #clustering #learning #relational
Relational co-clustering via manifold ensemble learning (PL, JB, CC, ZH), pp. 1687–1691.
CIKMCIKM-2012-LuZZX #image #learning #scalability #semantics #set
Semantic context learning with large-scale weakly-labeled image set (YL, WZ, KZ, XX), pp. 1859–1863.
CIKMCIKM-2012-MacdonaldSO #learning #on the #query #rank
On the usefulness of query features for learning to rank (CM, RLTS, IO), pp. 2559–2562.
CIKMCIKM-2012-MetzgerSHS #interactive #learning
LUKe and MIKe: learning from user knowledge and managing interactive knowledge extraction (SM, MS, KH, RS), pp. 2671–2673.
CIKMCIKM-2012-MorenoSRS #learning #multi #named
TALMUD: transfer learning for multiple domains (OM, BS, LR, GS), pp. 425–434.
CIKMCIKM-2012-NegahbanRG #learning #multi #performance #scalability #statistics #using
Scaling multiple-source entity resolution using statistically efficient transfer learning (SN, BIPR, JG), pp. 2224–2228.
CIKMCIKM-2012-QuanzH #generative #learning #multi #named
CoNet: feature generation for multi-view semi-supervised learning with partially observed views (BQ, JH), pp. 1273–1282.
CIKMCIKM-2012-RamanSGB #algorithm #learning #towards
Learning from mistakes: towards a correctable learning algorithm (KR, KMS, RGB, CJCB), pp. 1930–1934.
CIKMCIKM-2012-RenCJ #learning #topic
Topic based pose relevance learning in dance archives (RR, JPC, JMJ), pp. 2571–2574.
CIKMCIKM-2012-ShangJLW #learning
Learning spectral embedding via iterative eigenvalue thresholding (FS, LCJ, YL, FW), pp. 1507–1511.
CIKMCIKM-2012-SunG #learning
Active learning for relation type extension with local and global data views (AS, RG), pp. 1105–1112.
CIKMCIKM-2012-SunSL #learning #multi #performance #query
Fast multi-task learning for query spelling correction (XS, AS, PL), pp. 285–294.
CIKMCIKM-2012-SunWGM #hybrid #learning #rank #recommendation
Learning to rank for hybrid recommendation (JS, SW, BJG, JM), pp. 2239–2242.
CIKMCIKM-2012-VolkovsLZ #learning #rank
Learning to rank by aggregating expert preferences (MV, HL, RSZ), pp. 843–851.
CIKMCIKM-2012-WangC #learning #predict #word
Learning to predict the cost-per-click for your ad words (CJW, HHC), pp. 2291–2294.
CIKMCIKM-2012-WangH0 #framework #image #learning #mining #web
A unified learning framework for auto face annotation by mining web facial images (DW, SCHH, YH), pp. 1392–1401.
CIKMCIKM-2012-WangWYHDC #framework #learning #modelling #novel
A novel local patch framework for fixing supervised learning models (YW, BW, JY, YH, ZHD, ZC), pp. 1233–1242.
CIKMCIKM-2012-WangXY #learning
Importance weighted passive learning (SW, XX, YY), pp. 2243–2246.
CIKMCIKM-2012-YangTKZLDLW #learning #mining #network
Mining competitive relationships by learning across heterogeneous networks (YY, JT, JK, YZ, JL, YD, TL, LW), pp. 1432–1441.
CIKMCIKM-2012-YaoS #learning #relational #ubiquitous
Exploiting latent relevance for relational learning of ubiquitous things (LY, QZS), pp. 1547–1551.
CIKMCIKM-2012-ZhangHLL #learning #rank #realtime #twitter
Query-biased learning to rank for real-time twitter search (XZ, BH, TL, BL), pp. 1915–1919.
CIKMCIKM-2012-ZhangWW #framework #interactive #learning #ontology
An interaction framework of service-oriented ontology learning (JZ, YW, HW), pp. 2303–2306.
CIKMCIKM-2012-ZhouLZ #community #learning #quality
Joint relevance and answer quality learning for question routing in community QA (GZ, KL, JZ), pp. 1492–1496.
CIKMCIKM-2012-ZhouZ #debugging #learning #rank
Learning to rank duplicate bug reports (JZ, HZ), pp. 852–861.
ECIRECIR-2012-Lubell-DoughtieH #feedback #learning #rank
Learning to Rank from Relevance Feedback for e-Discovery (PLD, KH), pp. 535–539.
ECIRECIR-2012-LungleyKS #adaptation #domain model #interactive #learning #modelling #web
Learning Adaptive Domain Models from Click Data to Bootstrap Interactive Web Search (DL, UK, DS), pp. 527–530.
ICMLICML-2012-AzarMK #complexity #generative #learning #on the
On the Sample Complexity of Reinforcement Learning with a Generative Model (MGA, RM, BK), p. 222.
ICMLICML-2012-AzimiFFBH #coordination #learning
Batch Active Learning via Coordinated Matching (JA, AF, XZF, GB, BH), p. 44.
ICMLICML-2012-BalleQC #learning #modelling #optimisation
Local Loss Optimization in Operator Models: A New Insight into Spectral Learning (BB, AQ, XC), p. 236.
ICMLICML-2012-BelletHS #classification #learning #linear #similarity
Similarity Learning for Provably Accurate Sparse Linear Classification (AB, AH, MS), p. 193.
ICMLICML-2012-BonillaR #learning #probability #prototype
Discriminative Probabilistic Prototype Learning (EVB, ARK), p. 155.
ICMLICML-2012-BronsteinSS #learning #modelling #performance
Learning Efficient Structured Sparse Models (AMB, PS, GS), p. 33.
ICMLICML-2012-ChambersJ #learning
Learning the Central Events and Participants in Unlabeled Text (NC, DJ), p. 3.
ICMLICML-2012-CharlinZB #learning #problem
Active Learning for Matching Problems (LC, RSZ, CB), p. 23.
ICMLICML-2012-DekelTA #adaptation #learning #online #policy
Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret (OD, AT, RA), p. 227.
ICMLICML-2012-DuanXT #adaptation #learning
Learning with Augmented Features for Heterogeneous Domain Adaptation (LD, DX, IWT), p. 89.
ICMLICML-2012-DundarAQR #learning #modelling #online
Bayesian Nonexhaustive Learning for Online Discovery and Modeling of Emerging Classes (MD, FA, AQ, BR), p. 18.
ICMLICML-2012-EbanBSG #learning #online #predict #sequence
Learning the Experts for Online Sequence Prediction (EE, AB, SSS, AG), p. 38.
ICMLICML-2012-FarabetCNL #learning #multi #parsing
Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers (CF, CC, LN, YL), p. 241.
ICMLICML-2012-GeistSLG #approach #difference #learning
A Dantzig Selector Approach to Temporal Difference Learning (MG, BS, AL, MG), p. 49.
ICMLICML-2012-Gonen #kernel #learning #multi #performance
Bayesian Efficient Multiple Kernel Learning (MG), p. 17.
ICMLICML-2012-GongZM #learning #multi #robust
Robust Multiple Manifold Structure Learning (DG, XZ, GGM), p. 7.
ICMLICML-2012-GoodfellowCB #learning #scalability
Large-Scale Feature Learning With Spike-and-Slab Sparse Coding (IJG, ACC, YB), p. 180.
ICMLICML-2012-GuoX #classification #learning #multi
Cross Language Text Classification via Subspace Co-regularized Multi-view Learning (YG, MX), p. 120.
ICMLICML-2012-HanLC #learning #modelling #multi
Cross-Domain Multitask Learning with Latent Probit Models (SH, XL, LC), p. 51.
ICMLICML-2012-HazanK #learning #online
Projection-free Online Learning (EH, SK), p. 239.
ICMLICML-2012-HoiWZ #learning
Exact Soft Confidence-Weighted Learning (SCHH, JW, PZ), p. 19.
ICMLICML-2012-HoiWZJW #algorithm #bound #kernel #learning #online #performance #scalability
Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning (SCHH, JW, PZ, RJ, PW), p. 141.
ICMLICML-2012-Honorio #convergence #learning #modelling #optimisation #probability
Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising Models (JH), p. 144.
ICMLICML-2012-JalaliS #dependence #graph #learning
Learning the Dependence Graph of Time Series with Latent Factors (AJ, SS), p. 83.
ICMLICML-2012-JawanpuriaN #learning
A Convex Feature Learning Formulation for Latent Task Structure Discovery (PJ, JSN), p. 199.
ICMLICML-2012-JiangLS #3d #learning #using
Learning Object Arrangements in 3D Scenes using Human Context (YJ, ML, AS), p. 119.
ICMLICML-2012-JiYLJH #algorithm #bound #fault #learning
A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error Bound (MJ, TY, BL, RJ, JH), p. 110.
ICMLICML-2012-KalakrishnanRPS #learning #policy
Learning Force Control Policies for Compliant Robotic Manipulation (MK, LR, PP, SS), p. 10.
ICMLICML-2012-KarbasiIM #learning #rank
Comparison-Based Learning with Rank Nets (AK, SI, LM), p. 161.
ICMLICML-2012-KumarD #learning #multi
Learning Task Grouping and Overlap in Multi-task Learning (AK, HDI), p. 224.
ICMLICML-2012-KumarNKD #classification #framework #kernel #learning #multi
A Binary Classification Framework for Two-Stage Multiple Kernel Learning (AK, ANM, KK, HDI), p. 173.
ICMLICML-2012-KumarPK #learning #modelling #nondeterminism
Modeling Latent Variable Uncertainty for Loss-based Learning (MPK, BP, DK), p. 29.
ICMLICML-2012-LanctotGBB #game studies #learning
No-Regret Learning in Extensive-Form Games with Imperfect Recall (ML, RGG, NB, MB), p. 135.
ICMLICML-2012-LeRMDCCDN #learning #scalability #using
Building high-level features using large scale unsupervised learning (QVL, MR, RM, MD, GC, KC, JD, AYN), p. 69.
ICMLICML-2012-LinXWZ #learning
Total Variation and Euler’s Elastica for Supervised Learning (TL, HX, LW, HZ), p. 82.
ICMLICML-2012-LouH #learning
Structured Learning from Partial Annotations (XL, FAH), p. 52.
ICMLICML-2012-MakinoT #learning #parametricity
Apprenticeship Learning for Model Parameters of Partially Observable Environments (TM, JT), p. 117.
ICMLICML-2012-MatuszekFZBF #learning
A Joint Model of Language and Perception for Grounded Attribute Learning (CM, NF, LSZ, LB, DF), p. 186.
ICMLICML-2012-Memisevic #learning #multi #on the
On multi-view feature learning (RM), p. 140.
ICMLICML-2012-MnihH #image #learning #semistructured data
Learning to Label Aerial Images from Noisy Data (VM, GEH), p. 31.
ICMLICML-2012-MohamedHG #learning
Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning (SM, KAH, ZG), p. 91.
ICMLICML-2012-NiuDYS #learning #metric
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization (GN, BD, MY, MS), p. 136.
ICMLICML-2012-Painter-WakefieldP #algorithm #learning
Greedy Algorithms for Sparse Reinforcement Learning (CPW, RP), p. 114.
ICMLICML-2012-PassosRWD #flexibility #learning #modelling #multi
Flexible Modeling of Latent Task Structures in Multitask Learning (AP, PR, JW, HDI), p. 167.
ICMLICML-2012-PeharzP #learning #network
Exact Maximum Margin Structure Learning of Bayesian Networks (RP, FP), p. 102.
ICMLICML-2012-PiresS #estimation #learning #linear #statistics
Statistical linear estimation with penalized estimators: an application to reinforcement learning (BAP, CS), p. 228.
ICMLICML-2012-PlessisS #learning
Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching (MCdP, MS), p. 159.
ICMLICML-2012-PrasseSLS #email #identification #learning #regular expression
Learning to Identify Regular Expressions that Describe Email Campaigns (PP, CS, NL, TS), p. 146.
ICMLICML-2012-RossB #identification #learning #modelling
Agnostic System Identification for Model-Based Reinforcement Learning (SR, DB), p. 247.
ICMLICML-2012-SamdaniR #learning #performance #predict
Efficient Decomposed Learning for Structured Prediction (RS, DR), p. 200.
ICMLICML-2012-ScholkopfJPSZM #learning #on the
On causal and anticausal learning (BS, DJ, JP, ES, KZ, JMM), p. 63.
ICMLICML-2012-ShiS #adaptation #clustering #learning
Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation (YS, FS), p. 166.
ICMLICML-2012-ShivaswamyJ #learning #online #predict
Online Structured Prediction via Coactive Learning (PS, TJ), p. 12.
ICMLICML-2012-SilvaKB #learning
Learning Parameterized Skills (BCdS, GK, AGB), p. 187.
ICMLICML-2012-SohnL #invariant #learning
Learning Invariant Representations with Local Transformations (KS, HL), p. 174.
ICMLICML-2012-StorkeyMG #machine learning
Isoelastic Agents and Wealth Updates in Machine Learning Markets (AJS, JM, KG), p. 133.
ICMLICML-2012-Wagstaff #machine learning #matter
Machine Learning that Matters (KW), p. 240.
ICMLICML-2012-WangWHL #learning #monte carlo
Monte Carlo Bayesian Reinforcement Learning (YW, KSW, DH, WSL), p. 105.
ICMLICML-2012-XieHS #approach #automation #generative #learning
Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting (NX, HH, MS), p. 139.
ICMLICML-2012-XuWC #learning
The Greedy Miser: Learning under Test-time Budgets (ZEX, KQW, OC), p. 169.
ICMLICML-2012-YackleyL #learning
Smoothness and Structure Learning by Proxy (BY, TL), p. 57.
ICMLICML-2012-YangMJZZ #kernel #learning #multi #probability #programming
Multiple Kernel Learning from Noisy Labels by Stochastic Programming (TY, MM, RJ, LZ, YZ), p. 21.
ICMLICML-2012-ZhongK #clustering #flexibility #learning #multi
Convex Multitask Learning with Flexible Task Clusters (WZ, JTYK), p. 66.
ICPRICPR-2012-AbeOD #image #learning #rank
Recognizing surface qualities from natural images based on learning to rank (TA, TO, KD), pp. 3712–3715.
ICPRICPR-2012-AntoniukFH #learning #markov #network
Learning Markov Networks by Analytic Center Cutting Plane Method (KA, VF, VH), pp. 2250–2253.
ICPRICPR-2012-BaccoucheMWGB #2d #invariant #learning #recognition #representation #sequence
Sparse shift-invariant representation of local 2D patterns and sequence learning for human action recognition (MB, FM, CW, CG, AB), pp. 3823–3826.
ICPRICPR-2012-BaillyMPB #cost analysis #learning
Learning global cost function for face alignment (KB, MM, PP, EB), pp. 1112–1115.
ICPRICPR-2012-BanerjeeN #kernel #learning #multi #process #recognition #using
Pose based activity recognition using Multiple Kernel learning (PB, RN), pp. 445–448.
ICPRICPR-2012-CermanH #learning #problem
Tracking with context as a semi-supervised learning and labeling problem (LC, VH), pp. 2124–2127.
ICPRICPR-2012-ChernoffLN #fault #learning #metric
Metric learning by directly minimizing the k-NN training error (KC, ML, MN), pp. 1265–1268.
ICPRICPR-2012-DahmaneLDB #estimation #learning #symmetry
Learning symmetrical model for head pose estimation (AD, SL, CD, IMB), pp. 3614–3617.
ICPRICPR-2012-DAmbrosioIS #learning #re-engineering
A One-per-Class reconstruction rule for class imbalance learning (RD, GI, PS), pp. 1310–1313.
ICPRICPR-2012-DoTT #multi #representation #using
Text/graphic separation using a sparse representation with multi-learned dictionaries (THD, ST, ORT), pp. 689–692.
ICPRICPR-2012-DuanWLDC #learning #named
K-CPD: Learning of overcomplete dictionaries for tensor sparse coding (GD, HW, ZL, JD, YWC), pp. 493–496.
ICPRICPR-2012-FangZ #learning
I don’t know the label: Active learning with blind knowledge (MF, XZ), pp. 2238–2241.
ICPRICPR-2012-FiaschiKNH #learning
Learning to count with regression forest and structured labels (LF, UK, RN, FAH), pp. 2685–2688.
ICPRICPR-2012-GhanemKFZ #automation #learning #recognition
Context-aware learning for automatic sports highlight recognition (BG, MK, MF, TZ), pp. 1977–1980.
ICPRICPR-2012-GhoseMOMLFVCSM12a #3d #energy #framework #graph #learning #probability #segmentation
Graph cut energy minimization in a probabilistic learning framework for 3D prostate segmentation in MRI (SG, JM, AO, RM, XL, JF, JCV, JC, DS, FM), pp. 125–128.
ICPRICPR-2012-GranaCBC #image #learning #segmentation
Learning non-target items for interesting clothes segmentation in fashion images (CG, SC, DB, RC), pp. 3317–3320.
ICPRICPR-2012-GuK #learning #online #visual notation
Grassmann manifold online learning and partial occlusion handling for visual object tracking under Bayesian formulation (IYHG, ZHK), pp. 1463–1466.
ICPRICPR-2012-GutmannH #architecture #feature model #image #learning
Learning a selectivity-invariance-selectivity feature extraction architecture for images (MG, AH), pp. 918–921.
ICPRICPR-2012-HidoK #graph #learning #similarity
Hash-based structural similarity for semi-supervised Learning on attribute graphs (SH, HK), pp. 3009–3012.
ICPRICPR-2012-HinoO #kernel #learning #multi
An improved entropy-based multiple kernel learning (HH, TO), pp. 1189–1192.
ICPRICPR-2012-HiradeY #learning #predict
Ensemble learning for change-point prediction (RH, TY), pp. 1860–1863.
ICPRICPR-2012-HuangLT #invariant #learning #recognition
Learning modality-invariant features for heterogeneous face recognition (LH, JL, YPT), pp. 1683–1686.
ICPRICPR-2012-JinGYZ #algorithm #learning #multi
Multi-label learning vector quantization algorithm (XBJ, GG, JY, DZ), pp. 2140–2143.
ICPRICPR-2012-JiS12a #3d #estimation #learning #robust
Robust 3D human pose estimation via dual dictionaries learning (HJ, FS), pp. 3370–3373.
ICPRICPR-2012-KhanT #learning #taxonomy
Stable discriminative dictionary learning via discriminative deviation (NK, MFT), pp. 3224–3227.
ICPRICPR-2012-KongW #clustering #learning #multi
A multi-task learning strategy for unsupervised clustering via explicitly separating the commonality (SK, DW), pp. 771–774.
ICPRICPR-2012-KrijtheHL #classification #using
Improving cross-validation based classifier selection using meta-learning (JHK, TKH, ML), pp. 2873–2876.
ICPRICPR-2012-KumarRS #learning #predict
Learning to predict super resolution wavelet coefficients (NK, NKR, AS), pp. 3468–3471.
ICPRICPR-2012-KumarYD #classification #documentation #learning #retrieval
Learning document structure for retrieval and classification (JK, PY, DSD), pp. 1558–1561.
ICPRICPR-2012-LeeKD #induction #learning
Learning action symbols for hierarchical grammar induction (KL, TKK, YD), pp. 3778–3782.
ICPRICPR-2012-LiCHWM #3d #kernel #learning #multi #recognition
3D facial expression recognition via multiple kernel learning of Multi-Scale Local Normal Patterns (HL, LC, DH, YW, JMM), pp. 2577–2580.
ICPRICPR-2012-LiHL #adaptation #learning #multi #online #people
Online adaptive learning for multi-camera people counting (JL, LH, CL), pp. 3415–3418.
ICPRICPR-2012-LiLLL #distance #estimation #learning #metric
Learning distance metric regression for facial age estimation (CL, QL, JL, HL), pp. 2327–2330.
ICPRICPR-2012-LinLZ #learning #representation #taxonomy
Incoherent dictionary learning for sparse representation (TL, SL, HZ), pp. 1237–1240.
ICPRICPR-2012-LiPMH #classification #email #incremental #learning #using
Business email classification using incremental subspace learning (ML, YP, RM, HYH), pp. 625–628.
ICPRICPR-2012-LiuCSTN #learning #multi #performance #problem #recursion #scalability
Recursive NMF: Efficient label tree learning for large multi-class problems (LL, PMC, SS, PNT, AN), pp. 2148–2151.
ICPRICPR-2012-LiuL #analysis #detection #learning #multi
Unsupervised multi-target trajectory detection, learning and analysis in complicated environments (HL, JL), pp. 3716–3720.
ICPRICPR-2012-LiuLWZ #learning #linear
Locally linear embedding based example learning for pan-sharpening (QL, LL, YW, ZZ), pp. 1928–1931.
ICPRICPR-2012-LiuLYZ #composition #learning #visual notation
Learning to describe color composition of visual objects (YL, YL, ZY, NZ), pp. 3337–3340.
ICPRICPR-2012-LiuML #learning #multi
Training data recycling for multi-level learning (JL, SM, YL), pp. 2314–2318.
ICPRICPR-2012-LiuSW #learning #recognition #taxonomy
Facial expression recognition based on discriminative dictionary learning (WL, CS, YW), pp. 1839–1842.
ICPRICPR-2012-LiVBB #clustering #learning #using
Feature learning using Generalized Extreme Value distribution based K-means clustering (ZL, OV, HB, RB), pp. 1538–1541.
ICPRICPR-2012-LuLY #adaptation #classification #kernel #learning
Adaptive kernel learning based on centered alignment for hierarchical classification (YL, JL, JY), pp. 569–572.
ICPRICPR-2012-LuLZSCO #using
Learning-based deformable registration using weighted mutual information (YL, RL, LZ, YS, CC, SHO), pp. 2626–2629.
ICPRICPR-2012-MarcaciniCR #approach #clustering #learning
An active learning approach to frequent itemset-based text clustering (RMM, GNC, SOR), pp. 3529–3532.
ICPRICPR-2012-MogelmoseTM #comparative #dataset #detection #evaluation #learning
Learning to detect traffic signs: Comparative evaluation of synthetic and real-world datasets (AM, MMT, TBM), pp. 3452–3455.
ICPRICPR-2012-MoZW #classification #learning
Enhancing cross-view object classification by feature-based transfer learning (YM, ZZ, YW), pp. 2218–2221.
ICPRICPR-2012-Nagy #learning #web
Learning the characteristics of critical cells from web tables (GN), pp. 1554–1557.
ICPRICPR-2012-NamA #image #learning
Learning human preferences to sharpen images (MN, NA), pp. 2173–2176.
ICPRICPR-2012-NayefAB #learning
Learning feature weights of symbols, with application to symbol spotting (NN, MZA, TMB), pp. 2371–2374.
ICPRICPR-2012-Noh #analysis #classification #learning #metric #nearest neighbour
χ2 Metric learning for nearest neighbor classification and its analysis (SN), pp. 991–995.
ICPRICPR-2012-PangHYQW #analysis #classification #learning
Theoretical analysis of learning local anchors for classification (JP, QH, BY, LQ, DW), pp. 1803–1806.
ICPRICPR-2012-PanLS #kernel #learning
Learning kernels from labels with ideal regularization (BP, JHL, LS), pp. 505–508.
ICPRICPR-2012-PourdamghaniRZ #estimation #graph #learning #metric
Metric learning for graph based semi-supervised human pose estimation (NP, HRR, MZ), pp. 3386–3389.
ICPRICPR-2012-QinZCW #learning #online
Matting-driven online learning of Hough forests for object tracking (TQ, BZ, TJC, HW), pp. 2488–2491.
ICPRICPR-2012-San-BiagioUCCCM #approach #classification #kernel #learning #multi
A multiple kernel learning approach to multi-modal pedestrian classification (MSB, AU, MC, MC, UC, VM), pp. 2412–2415.
ICPRICPR-2012-SchauerteS #image #learning #modelling #robust #web
Learning robust color name models from web images (BS, RS), pp. 3598–3601.
ICPRICPR-2012-SharmaHN #classification #detection #incremental #learning #performance
Efficient incremental learning of boosted classifiers for object detection (PS, CH, RN), pp. 3248–3251.
ICPRICPR-2012-ShenMZ #analysis #graph #learning #online
Unsupervised online learning trajectory analysis based on weighted directed graph (YS, ZM, JZ), pp. 1306–1309.
ICPRICPR-2012-SommerFHG #detection #image
Learning-based mitotic cell detection in histopathological images (CS, LF, FAH, DG), pp. 2306–2309.
ICPRICPR-2012-SuLT #documentation #framework #image #learning #markov #random #using
A learning framework for degraded document image binarization using Markov Random Field (BS, SL, CLT), pp. 3200–3203.
ICPRICPR-2012-SunBM #learning
Unsupervised skeleton learning for manifold denoising (KS, EB, SMM), pp. 2719–2722.
ICPRICPR-2012-TabernikKBL #learning #low level #statistics #visual notation
Learning statistically relevant edge structure improves low-level visual descriptors (DT, MK, MB, AL), pp. 1471–1474.
ICPRICPR-2012-TangS #independence #learning #network #performance #testing #using
Efficient and accurate learning of Bayesian networks using chi-squared independence tests (YT, SNS), pp. 2723–2726.
ICPRICPR-2012-TiribuziPVR #detection #framework #kernel #learning #multi
A Multiple Kernel Learning framework for detecting altered fingerprints (MT, MP, PV, ER), pp. 3402–3405.
ICPRICPR-2012-TuS #adaptation #classification #learning
Dynamical ensemble learning with model-friendly classifiers for domain adaptation (WT, SS), pp. 1181–1184.
ICPRICPR-2012-VillamizarGSM #learning #online #random #using
Online human-assisted learning using Random Ferns (MV, AG, AS, FMN), pp. 2821–2824.
ICPRICPR-2012-VuralA #machine learning #video
A machine learning system for human-in-the-loop video surveillance (UV, YSA), pp. 1092–1095.
ICPRICPR-2012-WangJ12b #learning #network #process #recognition
Learning dynamic Bayesian network discriminatively for human activity recognition (XW, QJ), pp. 3553–3556.
ICPRICPR-2012-WangL12b #learning #recognition #string
String-level learning of confidence transformation for Chinese handwritten text recognition (DHW, CLL), pp. 3208–3211.
ICPRICPR-2012-WeberBLS #learning #segmentation
Unsupervised motion pattern learning for motion segmentation (MW, GB, ML, DS), pp. 202–205.
ICPRICPR-2012-XiaTWLL #categorisation #learning
Object categorization based on hierarchical learning (TX, YYT, YW, HL, LL), pp. 1419–1422.
ICPRICPR-2012-YangLZC #image #learning #multi #retrieval
Multi-view learning with batch mode active selection for image retrieval (WY, GL, LZ, EC), pp. 979–982.
ICPRICPR-2012-YanKMW #automation #game studies #learning
Automatic annotation of court games with structured output learning (FY, JK, KM, DW), pp. 3577–3580.
ICPRICPR-2012-YanRLS #classification #learning #multi
Active transfer learning for multi-view head-pose classification (YY, SR, OL, NS), pp. 1168–1171.
ICPRICPR-2012-YeD #learning #predict
Learning features for predicting OCR accuracy (PY, DSD), pp. 3204–3207.
ICPRICPR-2012-ZhangHR #classification #gender #learning
Hypergraph based semi-supervised learning for gender classification (ZZ, ERH, PR), pp. 1747–1750.
ICPRICPR-2012-ZhangZNH #learning #multi #recognition
Joint dynamic sparse learning and its application to multi-view face recognition (HZ, YZ, NMN, TSH), pp. 1671–1674.
ICPRICPR-2012-ZhaoSS #learning #predict
Importance-weighted label prediction for active learning with noisy annotations (LZ, GS, RS), pp. 3476–3479.
ICPRICPR-2012-ZhaoXY #learning #network #speech
Unsupervised Tibetan speech features Learning based on Dynamic Bayesian Networks (YZ, XX, GY), pp. 2319–2322.
ICPRICPR-2012-ZhaoYXJ #learning
A near-optimal non-myopic active learning method (YZ, GY, XX, QJ), pp. 1715–1718.
ICPRICPR-2012-ZhouWXZM #learning #recognition
Learning weighted features for human action recognition (WZ, CW, BX, ZZ, LM), pp. 1160–1163.
ICPRICPR-2012-ZhuoCQYX #algorithm #classification #image #learning #using
Image classification using HTM cortical learning algorithms (WZ, ZC, YQ, ZY, YX), pp. 2452–2455.
KDDKDD-2012-GongYZ #learning #multi #robust
Robust multi-task feature learning (PG, JY, CZ), pp. 895–903.
KDDKDD-2012-HalawiDGK #constraints #learning #scalability #word
Large-scale learning of word relatedness with constraints (GH, GD, EG, YK), pp. 1406–1414.
KDDKDD-2012-HoensC #learning
Learning in non-stationary environments with class imbalance (TRH, NVC), pp. 168–176.
KDDKDD-2012-JainVV #kernel #learning #multi #named
SPF-GMKL: generalized multiple kernel learning with a million kernels (AJ, SVNV, MV), pp. 750–758.
KDDKDD-2012-LiJPS #classification #learning #multi
Multi-domain active learning for text classification (LL, XJ, SJP, JTS), pp. 1086–1094.
KDDKDD-2012-Lin #case study #data mining #experience #machine learning #mining
Experiences and lessons in developing industry-strength machine learning and data mining software (CJL), p. 1176.
KDDKDD-2012-PatroDSWFK #approach #data-driven #how #learning #modelling #network
The missing models: a data-driven approach for learning how networks grow (RP, GD, ES, HW, DF, CK), pp. 42–50.
KDDKDD-2012-Posse #lessons learnt #network #recommendation #scalability #social
Key lessons learned building recommender systems for large-scale social networks (CP), p. 587.
KDDKDD-2012-RamanSJ #feedback #learning #online
Online learning to diversify from implicit feedback (KR, PS, TJ), pp. 705–713.
KDDKDD-2012-SeelandKK #clustering #graph #kernel #learning
A structural cluster kernel for learning on graphs (MS, AK, SK), pp. 516–524.
KDDKDD-2012-ShangJW #learning
Semi-supervised learning with mixed knowledge information (FS, LCJ, FW), pp. 732–740.
KDDKDD-2012-ShenJ #learning #recommendation #social
Learning personal + social latent factor model for social recommendation (YS, RJ), pp. 1303–1311.
KDDKDD-2012-SilvaC #learning #matrix #online
Active learning for online bayesian matrix factorization (JGS, LC), pp. 325–333.
KDDKDD-2012-SindhwaniG #distributed #learning #scalability #taxonomy
Large-scale distributed non-negative sparse coding and sparse dictionary learning (VS, AG), pp. 489–497.
KDDKDD-2012-TianZ #learning
Learning from crowds in the presence of schools of thought (YT, JZ), pp. 226–234.
KDDKDD-2012-XiongJXC #dependence #learning #metric #random
Random forests for metric learning with implicit pairwise position dependence (CX, DMJ, RX, JJC), pp. 958–966.
KDDKDD-2012-YuanWTNY #analysis #learning #multi
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data (LY, YW, PMT, VAN, JY), pp. 1149–1157.
KDDKDD-2012-ZhangH #induction #learning #multi
Inductive multi-task learning with multiple view data (JZ, JH), pp. 543–551.
KDDKDD-2012-ZhenY #learning #multimodal #probability
A probabilistic model for multimodal hash function learning (YZ, DYY), pp. 940–948.
KDDKDD-2012-ZhouKTX #machine learning
Adversarial support vector machine learning (YZ, MK, BMT, BX), pp. 1059–1067.
KDDKDD-2012-ZhouZ #collaboration #learning
Learning binary codes for collaborative filtering (KZ, HZ), pp. 498–506.
KDIRKDIR-2012-AbdullinN #clustering #data type #framework #learning
A Semi-supervised Learning Framework to Cluster Mixed Data Types (AA, ON), pp. 45–54.
KDIRKDIR-2012-BressoGDNS #3d #concept analysis #learning #relational
Formal Concept Analysis for the Interpretation of Relational Learning Applied on 3D Protein-binding Sites (EB, RG, MDD, AN, MST), pp. 111–120.
KDIRKDIR-2012-Dagnino #approach #grid #information management #machine learning #smarttech
Knowledge Discovery in the Smart Grid — A Machine Learning Approach (AD), pp. 366–369.
KDIRKDIR-2012-IkebeKT #learning #predict #smarttech #using
Friendship Prediction using Semi-supervised Learning of Latent Features in Smartphone Usage Data (YI, MK, HT), pp. 199–205.
KDIRKDIR-2012-LindnerH #constraints #learning #maintenance #parsing #random
Parsing and Maintaining Bibliographic References — Semi-supervised Learning of Conditional Random Fields with Constraints (SL, WH), pp. 233–238.
KEODKEOD-2012-GarciaAGG #case study #metadata #ontology
Case Study: Ontology for Metadata in e-Learning (AMFG, SSA, MEBG, RBG), pp. 317–320.
KEODKEOD-2012-RuizHM #education #evaluation #learning #ontology #quality
A New Proposal for Learning Objects Quality Evaluation in Learning Strategies based on Ontology for Education (LMGR, JMH, AMG), pp. 373–376.
KEODKEOD-2012-WohlgenanntWSS #learning #ontology #web
Confidence Management for Learning Ontologies from Dynamic Web Sources (GW, AW, AS, MS), pp. 172–177.
KMISKMIS-2012-AkiyoshiSK #learning #problem #towards
A Project Manager Skill-up Simulator Towards Problem Solving-based Learning (MA, MS, NK), pp. 190–195.
KMISKMIS-2012-AtkociunieneG #convergence #learning
Strategic Management, Learning and Innovation — Convergence of Strategic Management, Organizational Learning and Innovation: The Case of Lithuanian Organizations (ZA, IG), pp. 243–246.
KMISKMIS-2012-HackerMHHM #collaboration #learning
Management of Collaboration — Impacts of Virtualization to Learning & Knowledge (GH, MM, PH, GH, MM), pp. 235–239.
KMISKMIS-2012-HamadaAS #generative #learning #using
A Generation Method of Reference Operation using Reinforcement Learning on Project Manager Skill-up Simulator (KH, MA, MS), pp. 15–20.
KMISKMIS-2012-HubwieserM #collaboration #education #learning #network #ontology #social
A Social Network for Learning — Supporting Collaborative Learning based on the Ontology for Educational Knowledge (PH, AM), pp. 298–301.
KRKR-2012-BaralD #automation #how #learning #programming #set
Solving Puzzles Described in English by Automated Translation to Answer Set Programming and Learning How to Do that Translation (CB, JD).
MLDMMLDM-2012-BouhamedMLR #heuristic #learning #network
A New Learning Structure Heuristic of Bayesian Networks from Data (HB, AM, TL, AR), pp. 183–197.
MLDMMLDM-2012-ChanguelL #independence #machine learning #metadata #problem
Content Independent Metadata Production as a Machine Learning Problem (SC, NL), pp. 306–320.
MLDMMLDM-2012-HoaD #learning
A New Learning Strategy of General BAMs (NTH, TDB), pp. 213–221.
MLDMMLDM-2012-PitelisT #learning
Discriminant Subspace Learning Based on Support Vectors Machines (NP, AT), pp. 198–212.
MLDMMLDM-2012-TabatabaeiAKK #classification #internet #machine learning
Machine Learning-Based Classification of Encrypted Internet Traffic (TST, MA, FK, MK), pp. 578–592.
MLDMMLDM-2012-ToussaintB #comparison #empirical #learning
Proximity-Graph Instance-Based Learning, Support Vector Machines, and High Dimensionality: An Empirical Comparison (GTT, CB), pp. 222–236.
MLDMMLDM-2012-XuCG #concept #learning #multi #using
Constructing Target Concept in Multiple Instance Learning Using Maximum Partial Entropy (TX, DKYC, IG), pp. 169–182.
RecSysRecSys-2012-DeDGM #difference #learning #using
Local learning of item dissimilarity using content and link structure (AD, MSD, NG, PM), pp. 221–224.
RecSysRecSys-2012-Herbrich #distributed #learning #online #realtime
Distributed, real-time bayesian learning in online services (RH), pp. 203–204.
RecSysRecSys-2012-KarimiFNS #learning #matrix #recommendation
Exploiting the characteristics of matrix factorization for active learning in recommender systems (RK, CF, AN, LST), pp. 317–320.
RecSysRecSys-2012-Kohavi #online #statistics
Online controlled experiments: introduction, learnings, and humbling statistics (RK), pp. 1–2.
RecSysRecSys-2012-SalimansPG #collaboration #learning #ranking
Collaborative learning of preference rankings (TS, UP, TG), pp. 261–264.
RecSysRecSys-2012-ShiKBLOH #collaboration #learning #named #rank
CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering (YS, AK, LB, ML, NO, AH), pp. 139–146.
SEKESEKE-2012-AlawawdehAL #adaptation #collaboration #learning #named
CLAT: Collaborative Learning Adaptive Tutor (AMHA, CA, LL), pp. 747–752.
SEKESEKE-2012-DagninoSR #fault #machine learning #using
Forecasting Fault Events in Power Distribution Grids Using Machine Learning (AD, KS, LR), pp. 458–463.
SEKESEKE-2012-El-SherifFE #concept #learning #multi #network #social #using
Using Social Networks for Learning New Concepts in Multi-Agent Systems (SMES, BHF, AE), pp. 261–266.
SEKESEKE-2012-HaoWZ #classification #empirical #machine learning
An Empirical Study of Execution-Data Classification Based on Machine Learning (DH, XW, LZ), pp. 283–288.
SEKESEKE-2012-XavierOC #fuzzy #learning #logic
Evolutionary Learning and Fuzzy Logic Applied to a Load Balancer (FCX, MGdO, CLdC), pp. 256–260.
SEKESEKE-2012-XiePDMRTR #categorisation #clustering #grid #power management
Progressive Clustering with Learned Seeds: An Event Categorization System for Power Grid (BX, RJP, HD, JYM, AR, AT, CR), pp. 100–105.
SEKESEKE-2012-Zhang #bias #learning #named
i2Learning: Perpetual Learning through Bias Shifting (DZ), pp. 249–255.
SIGIRSIGIR-2012-BilgicB #learning #query
Active query selection for learning rankers (MB, PNB), pp. 1033–1034.
SIGIRSIGIR-2012-ChangHYLC #ranking #web
Learning-based time-sensitive re-ranking for web search (PTC, YCH, CLY, SDL, PJC), pp. 1101–1102.
SIGIRSIGIR-2012-GaoWL #graph #information retrieval #learning #mining #scalability
Large-scale graph mining and learning for information retrieval (BG, TW, TYL), pp. 1194–1195.
SIGIRSIGIR-2012-HongBAD #learning #rank #social
Learning to rank social update streams (LH, RB, JA, BDD), pp. 651–660.
SIGIRSIGIR-2012-JiangWLAW #alias #approach #detection #learning #similarity #string #towards
Towards alias detection without string similarity: an active learning based approach (LJ, JW, PL, NA, MW), pp. 1155–1156.
SIGIRSIGIR-2012-KanhabuaBN #learning #retrieval
Learning to select a time-aware retrieval model (NK, KB, KN), pp. 1099–1100.
SIGIRSIGIR-2012-KovesiGA #categorisation #learning #multi #online #performance
Fast on-line learning for multilingual categorization (MK, CG, MRA), pp. 1071–1072.
SIGIRSIGIR-2012-LiX #machine learning #web
Beyond bag-of-words: machine learning for query-document matching in web search (HL, JX), p. 1177.
SIGIRSIGIR-2012-MacdonaldTO #learning #online #predict #query #scheduling
Learning to predict response times for online query scheduling (CM, NT, IO), pp. 621–630.
SIGIRSIGIR-2012-MacdonaldTO12a #effectiveness #learning #rank #safety
Effect of dynamic pruning safety on learning to rank effectiveness (CM, NT, IO), pp. 1051–1052.
SIGIRSIGIR-2012-NiuGLC #evaluation #learning #rank #ranking
Top-k learning to rank: labeling, ranking and evaluation (SN, JG, YL, XC), pp. 751–760.
SIGIRSIGIR-2012-OzertemCDV #framework #machine learning #query #ranking
Learning to suggest: a machine learning framework for ranking query suggestions (UO, OC, PD, EV), pp. 25–34.
SIGIRSIGIR-2012-SeverynM #learning #ranking #scalability
Structural relationships for large-scale learning of answer re-ranking (AS, AM), pp. 741–750.
SIGIRSIGIR-2012-ZhangWDH #detection #learning #performance #reuse
Learning hash codes for efficient content reuse detection (QZ, YW, ZD, XH), pp. 405–414.
OOPSLAOOPSLA-2012-KulkarniC #compilation #machine learning #optimisation #problem #using
Mitigating the compiler optimization phase-ordering problem using machine learning (SK, JC), pp. 147–162.
OOPSLAOOPSLA-2012-St-AmourTF #communication #optimisation
Optimization coaching: optimizers learn to communicate with programmers (VSA, STH, MF), pp. 163–178.
TOOLSTOOLS-EUROPE-2012-Sureka #component #debugging #learning
Learning to Classify Bug Reports into Components (AS), pp. 288–303.
PADLPADL-2012-ZhuFW #ad hoc #incremental
LearnPADS + + : Incremental Inference of Ad Hoc Data Formats (KQZ, KF, DW), pp. 168–182.
REFSQREFSQ-2012-EngelsmanW #architecture #case study #enterprise #lessons learnt #requirements
Goal-Oriented Requirements Engineering and Enterprise Architecture: Two Case Studies and Some Lessons Learned (WE, RW), pp. 306–320.
REFSQREFSQ-2012-KnaussS #documentation #heuristic #learning #requirements
Supporting Learning Organisations in Writing Better Requirements Documents Based on Heuristic Critiques (EK, KS), pp. 165–171.
SACSAC-2012-MinervinidF #concept #learning #logic #probability
Learning probabilistic Description logic concepts: under different Assumptions on missing knowledge (PM, Cd, NF), pp. 378–383.
SACSAC-2012-NunesCM #learning #network #similarity #social
Resolving user identities over social networks through supervised learning and rich similarity features (AN, PC, BM), pp. 728–729.
SACSAC-2012-OongI #classification #fuzzy #learning #multi #performance #testing
Multilayer Fuzzy ARTMAP: fast learning and fast testing for pattern classification (THO, NAMI), pp. 27–32.
ICSEICSE-2012-Chioasca #automation #machine learning #model transformation #requirements #using
Using machine learning to enhance automated requirements model transformation (EVC), pp. 1487–1490.
ICSEICSE-2012-DagenaisR #api #learning #traceability
Recovering traceability links between an API and its learning resources (BD, MPR), pp. 47–57.
ICSEICSE-2012-FengC #behaviour #learning #multi
Multi-label software behavior learning (YF, ZC), pp. 1305–1308.
ICSEICSE-2012-GrechanikFX #automation #learning #performance #problem #testing
Automatically finding performance problems with feedback-directed learning software testing (MG, CF, QX), pp. 156–166.
ICSEICSE-2012-StaatsGH #automation #fault #how #mutation testing #testing
Automated oracle creation support, or: How I learned to stop worrying about fault propagation and love mutation testing (MS, GG, MPEH), pp. 870–880.
CAVCAV-2012-ChenW #incremental #learning
Learning Boolean Functions Incrementally (YFC, BYW), pp. 55–70.
CAVCAV-2012-LeeWY #algorithm #analysis #learning #termination
Termination Analysis with Algorithmic Learning (WL, BYW, KY), pp. 88–104.
CAVCAV-2012-SinhaSCS
Alternate and Learn: Finding Witnesses without Looking All over (NS, NS, SC, MS), pp. 599–615.
CSLCSL-2012-Berardid #learning
Knowledge Spaces and the Completeness of Learning Strategies (SB, Ud), pp. 77–91.
ICLPICLP-2012-BlockeelBBCP #data mining #machine learning #mining #modelling #problem
Modeling Machine Learning and Data Mining Problems with FO(·) (HB, BB, MB, BdC, SDP, MD, AL, JR, SV), pp. 14–25.
ICLPICLP-2012-MarateaPR #machine learning
Applying Machine Learning Techniques to ASP Solving (MM, LP, FR), pp. 37–48.
ICSTICST-2012-RamlerKP #combinator #design #lessons learnt
Combinatorial Test Design in the TOSCA Testsuite: Lessons Learned and Practical Implications (RR, TK, WP), pp. 569–572.
ICSTICST-2012-SunSPR #cost analysis #learning #named #reliability
CARIAL: Cost-Aware Software Reliability Improvement with Active Learning (BS, GS, AP, SR), pp. 360–369.
ICTSSICTSS-2012-StrugS #approach #machine learning #mutation testing #testing
Machine Learning Approach in Mutation Testing (JS, BS), pp. 200–214.
ICTSSICTSS-2012-Vaandrager #finite #learning #state machine
Active Learning of Extended Finite State Machines (FWV), pp. 5–7.
LICSLICS-2012-KomuravelliPC #learning #probability
Learning Probabilistic Systems from Tree Samples (AK, CSP, EMC), pp. 441–450.
ICSTSAT-2012-BonetB #learning
An Improved Separation of Regular Resolution from Pool Resolution and Clause Learning (MLB, SRB), pp. 44–57.
ICSTSAT-2012-KatsirelosS #learning #satisfiability
Learning Polynomials over GF(2) in a SAT Solver — (Poster Presentation) (GK, LS), pp. 496–497.
ICSTSAT-2012-LaitinenJN #learning
Conflict-Driven XOR-Clause Learning (TL, TAJ, IN), pp. 383–396.
ICSTSAT-2012-MatsliahSS #learning
Augmenting Clause Learning with Implied Literals — (Poster Presentation) (AM, AS, HS), pp. 500–501.
ICSTSAT-2012-SabharwalSS #learning #satisfiability
Learning Back-Clauses in SAT — (Poster Presentation) (AS, HS, MS), pp. 498–499.
SMTSMT-2012-AzizWD #estimation #machine learning #problem #smt
A Machine Learning Technique for Hardness Estimation of QFBV SMT Problems (MAA, AGW, NMD), pp. 57–66.
CBSECBSE-2011-AletiM #component #deployment #learning #optimisation
Component deployment optimisation with bayesian learning (AA, IM), pp. 11–20.
ECSAECSA-2011-JrCCGOFMG #architecture #component #lessons learnt #product line #uml
Extending UML Components to Develop Software Product-Line Architectures: Lessons Learned (ACCJ, GGC, TEC, IMdSG, EAOJ, SF, PCM, AFG), pp. 130–138.
ASEASE-2011-ChenHX #approach #evaluation #machine learning #process
Software process evaluation: A machine learning approach (NC, SCHH, XX), pp. 333–342.
DACDAC-2011-DingGYP #detection #learning #named
AENEID: a generic lithography-friendly detailed router based on post-RET data learning and hotspot detection (DD, JRG, KY, DZP), pp. 795–800.
DACDAC-2011-GeQ #machine learning #multi #using
Dynamic thermal management for multimedia applications using machine learning (YG, QQ), pp. 95–100.
DACDAC-2011-KatzRZS #architecture #behaviour #generative #learning #quality
Learning microarchitectural behaviors to improve stimuli generation quality (YK, MR, AZ, GS), pp. 848–853.
DACDAC-2011-WangXAP #classification #learning #policy #power management #using
Deriving a near-optimal power management policy using model-free reinforcement learning and Bayesian classification (YW, QX, ACA, MP), pp. 41–46.
DATEDATE-2011-ArslanO #adaptation #effectiveness #learning #optimisation #realtime
Adaptive test optimization through real time learning of test effectiveness (BA, AO), pp. 1430–1435.
DocEngDocEng-2011-ChidlovskiiB #learning #metric #network #recommendation #social
Local metric learning for tag recommendation in social networks (BC, AB), pp. 205–208.
ICDARICDAR-2011-CoatesCCSSWWN #detection #image #learning #recognition
Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning (AC, BC, CC, SS, BS, TW, DJW, AYN), pp. 440–445.
ICDARICDAR-2011-KumarPD #classification #documentation #image #learning #multi #using
Document Image Classification and Labeling Using Multiple Instance Learning (JK, JP, DSD), pp. 1059–1063.
ICDARICDAR-2011-ShaoWXZZ11a #learning #multi
Multiple Instance Learning Based Method for Similar Handwritten Chinese Characters Discrimination (YS, CW, BX, RZ, YZ), pp. 1002–1006.
ICDARICDAR-2011-SuLZ #learning #polynomial
Perceptron Learning of Modified Quadratic Discriminant Function (THS, CLL, XYZ), pp. 1007–1011.
ICDARICDAR-2011-TaoLJG #learning #locality #recognition #using
Similar Handwritten Chinese Character Recognition Using Discriminative Locality Alignment Manifold Learning (DT, LL, LJ, YG), pp. 1012–1016.
ICDARICDAR-2011-VajdaJF #approach #learning
A Semi-supervised Ensemble Learning Approach for Character Labeling with Minimal Human Effort (SV, AJ, GAF), pp. 259–263.
ICDARICDAR-2011-WangDL #learning #recognition
MQDF Discriminative Learning Based Offline Handwritten Chinese Character Recognition (YW, XD, CL), pp. 1100–1104.
SIGMODSIGMOD-2011-GetoorM #learning #modelling #relational #statistics
Learning statistical models from relational data (LG, LM), pp. 1195–1198.
CSEETCSEET-2011-AndrianoMBR #assessment
A quantitative assessment method for simulation-based e-learnings (NA, MGM, CB, DR), pp. 159–168.
CSEETCSEET-2011-ChimalakondaN #education #learning #question #re-engineering
Can we make software engineering education better by applying learning theories? (SC, KVN), p. 561.
CSEETCSEET-2011-EngM #assessment #communication #experience #learning #student
Continued assessment of students’ learning experience in an oral communication course at MIT for EECS majors (TLE, RM), pp. 439–443.
CSEETCSEET-2011-GalvaoARAFG #education #learning #logic programming #process
A proposal for an educational system service to support teaching/learning process for logic programming (ERDG, RRdA, CMOR, SCA, FF, VCG), p. 556.
CSEETCSEET-2011-Garousi #challenge #industrial #lessons learnt #testing
Incorporating real-world industrial testing projects in software testing courses: Opportunities, challenges, and lessons learned (VG), pp. 396–400.
CSEETCSEET-2011-GimenesBB #distance #learning #re-engineering #source code
International workshop on distance learning support for postgraduate programs in software engineering (e-gradSE) (IMdSG, LB, EFB), pp. 517–519.
CSEETCSEET-2011-HattoriBLL #game studies #learning
Erase and rewind — Learning by replaying examples (LH, AB, ML, ML), p. 558.
CSEETCSEET-2011-HoskingSKJ #learning #re-engineering #student
Learning at the elbows of experts: Technology roadmapping with Software Engineering students (JGH, PS, EK, NJ), pp. 139–148.
CSEETCSEET-2011-RichardsonRSPD #learning #problem #quality #research
Educating software engineers of the future: Software quality research through problem-based learning (IR, LR, SBS, BP, YD), pp. 91–100.
CSEETCSEET-2011-TillmannHX #education #game studies #learning #named #social
Pex4Fun: Teaching and learning computer science via social gaming (NT, JdH, TX), pp. 546–548.
CSEETCSEET-2011-TuTOBHKY #learning
Turning real-world systems into verification-driven learning cases (ST, ST, SO, BB, BH, AK, ZY), pp. 129–138.
CSEETCSEET-2011-Virseda #education #learning #re-engineering #semantics
A learning methodology based on semantic tableaux for software engineering education (RdVV), pp. 401–405.
CSEETCSEET-2011-WongBDMOV #case study #education #experience #lessons learnt #testing
Teaching software testing: Experiences, lessons learned and the path forward (WEW, AB, VD, APM, JO, MAV), pp. 530–534.
ITiCSEITiCSE-2011-AnjorinGR #collaboration #framework #learning #named #web
CROKODIL: a platform supporting the collaborative management of web resources for learning purposes (MA, RDG, CR), p. 361.
ITiCSEITiCSE-2011-BowerM #comparison #learning
Continual and explicit comparison to promote proactive facilitation during second computer language learning (MB, AM), pp. 218–222.
ITiCSEITiCSE-2011-BoyceCPCB #education #evaluation #game studies #how #learning #motivation
Experimental evaluation of BeadLoom game: how adding game elements to an educational tool improves motivation and learning (AKB, AC, SP, DC, TB), pp. 243–247.
ITiCSEITiCSE-2011-CamachoM #learning #programming
Facilitating learning dynamic programming through a previous introduction of exhaustive search (AC, AM), p. 355.
ITiCSEITiCSE-2011-ChanK
Do educational software systems provide satisfactory learning opportunities for “multi-sensory learning” methodology? (PC, GK), p. 358.
ITiCSEITiCSE-2011-ChuaB #framework
Integrating scholarly articles within e-learning courses: a framework (BBC, DVB), p. 392.
ITiCSEITiCSE-2011-EllisH #learning #named #student
Courseware: student learning via FOSS field trips (HJCE, GWH), p. 329.
ITiCSEITiCSE-2011-GarciaMGH #interface #learning #unification
A system for usable unification of interfaces of learning objects in m-learning (EG, LdM, AGC, JRH), p. 347.
ITiCSEITiCSE-2011-Goldweber #learning #process #turing machine
Two kinesthetic learning activities: turing machines and basic computer organization (MG), p. 335.
ITiCSEITiCSE-2011-Goldweber11a #learning #social
Computing for the social good: a service learning project (MG), p. 379.
ITiCSEITiCSE-2011-HarrachA #collaboration #learning #optimisation #process #recommendation #using
Optimizing collaborative learning processes by using recommendation systems (SH, MA), p. 389.
ITiCSEITiCSE-2011-Hijon-NeiraV11a #design #learning
A first step mapping IMS learning design and Merlin-Mo (RHN, JÁVI), p. 365.
ITiCSEITiCSE-2011-HoverHR #collaboration #learning
A collaborative linked learning space (KMH, MH, GR), p. 380.
ITiCSEITiCSE-2011-HoverHRM #collaboration #how #learning #student
Evaluating how students would use a collaborative linked learning space (KMH, MH, GR, MM), pp. 88–92.
ITiCSEITiCSE-2011-JourjonKY #framework
Impact of an e-learning platform on CSE lectures (GJ, SSK, JY), pp. 83–87.
ITiCSEITiCSE-2011-KonertRGSB #ad hoc #community #learning
Supporting peer learning with ad-hoc communities (JK, KR, SG, RS, RB), p. 393.
ITiCSEITiCSE-2011-LasserreS #learning
Effects of team-based learning on a CS1 course (PL, CS), pp. 133–137.
ITiCSEITiCSE-2011-LuLJZJ #student
A bioinformatics e-learning lab for undergraduate students (FL, HL, YJ, YZ, ZJ), p. 356.
ITiCSEITiCSE-2011-MartinezC #algebra #education #relational
A cooperative learning-based strategy for teaching relational algebra (AM, AC), pp. 263–267.
ITiCSEITiCSE-2011-MesserK #problem #process
The use of mediating artifacts in embedding problem solving processes in an e-learning environment (OMM, AK), p. 390.
ITiCSEITiCSE-2011-MothVB #learning #named #syntax
SyntaxTrain: relieving the pain of learning syntax (ALAM, JV, MBA), p. 387.
ITiCSEITiCSE-2011-OliveiraMR #learning #problem #programming
From concrete to abstract?: problem domain in the learning of introductory programming (OLO, AMM, NTR), pp. 173–177.
ITiCSEITiCSE-2011-PollockH #learning #multi
Combining multiple pedagogies to boost learning and enthusiasm (LLP, TH), pp. 258–262.
ITiCSEITiCSE-2011-RussellMD #approach #learning #student
A contextualized project-based approach for improving student engagement and learning in AI courses (IR, ZM, JD), p. 368.
ITiCSEITiCSE-2011-Sanchez-TorrubiaTT #algorithm #assessment #automation #learning
GLMP for automatic assessment of DFS algorithm learning (MGST, CTB, GT), p. 351.
ITiCSEITiCSE-2011-ShuhidanHD #comprehension #learning
Understanding novice programmer difficulties via guided learning (SMS, MH, DJD), pp. 213–217.
ITiCSEITiCSE-2011-VanoM #learning #quote
“Computer science and nursery rhymes”: a learning path for the middle school (DDV, CM), pp. 238–242.
ITiCSEITiCSE-2011-WolzMS #learning #process
Kinesthetic learning of computing via “off-beat” activities (UW, MM, MS), pp. 68–72.
ESOPESOP-2011-BorgstromGGMG #machine learning #semantics
Measure Transformer Semantics for Bayesian Machine Learning (JB, ADG, MG, JM, JVG), pp. 77–96.
FASEFASE-2011-FengKP #automation #composition #learning #probability #reasoning
Automated Learning of Probabilistic Assumptions for Compositional Reasoning (LF, MZK, DP), pp. 2–17.
TACASTACAS-2011-JungLWY #generative #invariant #quantifier
Predicate Generation for Learning-Based Quantifier-Free Loop Invariant Inference (YJ, WL, BYW, KY), pp. 205–219.
TACASTACAS-2011-MertenSHM #generative
Next Generation LearnLib (MM, BS, FH, TMS), pp. 220–223.
ICPCICPC-J-2009-Sanz-RodriguezDA11 #evaluation #learning #reuse
Metrics-based evaluation of learning object reusability (JSR, JMD, SSA), pp. 121–140.
CSMRCSMR-2011-Borchers #assessment #re-engineering
Invited Talk: Reengineering from a Practitioner’s View — A Personal Lesson’s Learned Assessment (JB), pp. 1–2.
SASSAS-2011-NoriR #machine learning #program analysis
Program Analysis and Machine Learning: A Win-Win Deal (AVN, SKR), pp. 2–3.
STOCSTOC-2011-BalcanH #learning
Learning submodular functions (MFB, NJAH), pp. 793–802.
DLTDLT-2011-Yoshinaka #concept #context-free grammar #learning #towards
Towards Dual Approaches for Learning Context-Free Grammars Based on Syntactic Concept Lattices (RY), pp. 429–440.
ICALPICALP-v1-2011-AroraG #algorithm #fault #learning
New Algorithms for Learning in Presence of Errors (SA, RG), pp. 403–415.
ICALPICALP-v1-2011-HarkinsH #algorithm #bound #game studies #learning
Exact Learning Algorithms, Betting Games, and Circuit Lower Bounds (RCH, JMH), pp. 416–423.
LATALATA-2011-CaseJLOSS #automation #learning #pattern matching #subclass
Automatic Learning of Subclasses of Pattern Languages (JC, SJ, TDL, YSO, PS, FS), pp. 192–203.
SFMSFM-2011-Jonsson #automaton #learning #modelling
Learning of Automata Models Extended with Data (BJ), pp. 327–349.
SFMSFM-2011-Moschitti #automation #kernel #learning #modelling
Kernel-Based Machines for Abstract and Easy Modeling of Automatic Learning (AM), pp. 458–503.
SFMSFM-2011-SteffenHM #automaton #learning #perspective
Introduction to Active Automata Learning from a Practical Perspective (BS, FH, MM), pp. 256–296.
CHICHI-2011-ChauKHF #interactive #machine learning #named #network #scalability
Apolo: making sense of large network data by combining rich user interaction and machine learning (DHC, AK, JIH, CF), pp. 167–176.
CHICHI-2011-DavidoffZZD #coordination #learning #product line
Learning patterns of pick-ups and drop-offs to support busy family coordination (SD, BDZ, JZ, AKD), pp. 1175–1184.
CHICHI-2011-EdgeSCZL #learning #mobile #named
MicroMandarin: mobile language learning in context (DE, ES, KC, JZ, JAL), pp. 3169–3178.
CHICHI-2011-FiebrinkCT #evaluation #interactive #learning
Human model evaluation in interactive supervised learning (RF, PRC, DT), pp. 147–156.
CHICHI-2011-HowisonTRA #concept #interactive #learning
The mathematical imagery trainer: from embodied interaction to conceptual learning (MH, DT, DR, DA), pp. 1989–1998.
CHICHI-2011-JamilOPKS #collaboration #interactive #learning
The effects of interaction techniques on talk patterns in collaborative peer learning around interactive tables (IJ, KO, MJP, AK, SS), pp. 3043–3052.
CHICHI-2011-LindenJBRS #feedback #game studies #lessons learnt #realtime
Buzzing to play: lessons learned from an in the wild study of real-time vibrotactile feedback (JvdL, RMGJ, JB, YR, ES), pp. 533–542.
CHICHI-2011-MoravejiMMCR #development #learning #named #social #web
ClassSearch: facilitating the development of web search skills through social learning (NM, MRM, DM, MC, NHR), pp. 1797–1806.
CHICHI-2011-ShaerSVFLW #interactive #learning
Enhancing genomic learning through tabletop interaction (OS, MS, CV, TF, ML, HW), pp. 2817–2826.
CHICHI-2011-ToupsKHS #coordination #learning #simulation
Zero-fidelity simulation of fire emergency response: improving team coordination learning (ZOT, AK, WAH, NS), pp. 1959–1968.
CHICHI-2011-TrustyT #learning #web
Augmenting the web for second language vocabulary learning (AT, KNT), pp. 3179–3188.
CSCWCSCW-2011-NawahdahI #automation #education #learning
Automatic adjustment of a virtual teacher’s model in a learning support system (MN, TI), pp. 693–696.
HCIDHM-2011-EilersM #composition #learning #modelling #using
Learning the Relevant Percepts of Modular Hierarchical Bayesian Driver Models Using a Bayesian Information Criterion (ME, CM), pp. 463–472.
HCIDHM-2011-TangwenF #analysis #architecture #cumulative #learning #polymorphism
Polymorphic Cumulative Learning in Integrated Cognitive Architectures for Analysis of Pilot-Aircraft Dynamic Environment (TY, SF), pp. 409–416.
HCIDUXU-v1-2011-BjorndalRM #industrial #lessons learnt #requirements #specification #using
Lessons Learned from Using Personas and Scenarios for Requirements Specification of Next-Generation Industrial Robots (PB, MJR, SM), pp. 378–387.
HCIDUXU-v1-2011-ChenT #design #industrial #learning #problem #student
Exploring the Learning Problems and Resources Usage of Undergraduate Industrial Design Students in Design Studio (WC, HHT), pp. 43–52.
HCIDUXU-v1-2011-GeorgeADMW #collaboration #learning #multi
Multitouch Tables for Collaborative Object-Based Learning (JG, EdA, DD, DSM, GW), pp. 237–246.
HCIDUXU-v1-2011-Innes #design #enterprise #why
Why Enterprises Can’t Innovate: Helping Companies Learn Design Thinking (JI), pp. 442–448.
HCIDUXU-v1-2011-LeeR #architecture #collaboration #concept #learning #mobile
Suggested Collaborative Learning Conceptual Architecture and Applications for Mobile Devices (KL, AR), pp. 611–620.
HCIDUXU-v1-2011-Schmid #analysis #development #feedback #learning
Development of an Augmented Feedback Application to Support Motor Learning after Stroke: Requirement Analysis (SS), pp. 305–314.
HCIDUXU-v2-2011-ArditoLRSYAC #design #game studies #learning #pervasive
Designing Pervasive Games for Learning (CA, RL, DR, CS, NY, NMA, MFC), pp. 99–108.
HCIHCD-2011-ChoiS #approach #design #implementation #process
A Design-Supporting Tool for Implementing the Learning-Based Approach: Accommodating Users’ Domain Knowledge into Design Processes (JMC, KS), pp. 369–378.
HCIHCD-2011-KamihiraAN #communication #community #design #education #learning #visual notation
Building a Shared Cross-Cultural Learning Community for Visual Communication Design Education (TK, MA, TN), pp. 397–406.
HCIHCI-MIIE-2011-KarthikP #adaptation #approach #classification #email #machine learning
Adaptive Machine Learning Approach for Emotional Email Classification (KK, RP), pp. 552–558.
HCIHCI-MIIE-2011-MajimaNMHNHA #evaluation #learning #mobile
Evaluation of Continuous Practice by Mobile Learning in Nursing Practical Training (YM, YN, YM, MH, YN, SH, HA), pp. 84–91.
HCIHCI-UA-2011-AdamsS #learning
A Web-Based Learning Environment to Support Chemistry (CA, CS), pp. 3–11.
HCIHCI-UA-2011-EverardJM #learning #question #student #what
Are MIS Students Learning What They Need to Land a Job? (AE, BMJ, SM), pp. 235–236.
HCIHCI-UA-2011-GeorgeS #collaboration #game studies #learning
Introducing Mobility in Serious Games: Enhancing Situated and Collaborative Learning (SG, AS), pp. 12–20.
HCIHCI-UA-2011-HayakawaNOFN #framework #learning #visualisation
Visualization Framework for Computer System Learning (EH, YN, HO, MF, YN), pp. 21–26.
HCIHCI-UA-2011-Huseyinov #adaptation #fuzzy #learning #modelling #multi
Fuzzy Linguistic Modelling Cognitive / Learning Styles for Adaptation through Multi-level Granulation (IH), pp. 39–47.
HCIHCI-UA-2011-Klenner-Moore #learning #process
Creating a New Context for Activity in Blended Learning Environments: Engaging the Twitchy Fingers (JKM), pp. 61–67.
HCIHCI-UA-2011-LiJN #learning #user interface #visual notation
Haptically Enhanced User Interface to Support Science Learning of Visually Impaired (YL, SLJ, CSN), pp. 68–76.
HCIHCI-UA-2011-NagaiKI #learning #process
A Drawing Learning Support System with Auto-evaluating Function Based on the Drawing Process Model (TN, MK, KI), pp. 97–106.
HCIHCI-UA-2011-Wang11a #interactive #learning #network #student #tool support #using
Interactions between Human and Computer Networks: EFL College Students Using Computer Learning Tools in Remedial English Classes (ALW), pp. 107–112.
HCIHCI-UA-2011-YajimaT #collaboration #learning
Proposal of Collaborative Learning Support Method in Risk Communications (HY, NT), pp. 113–120.
HCIHCI-UA-2011-YamaguchiMT #evaluation #learning #online
Evaluation of Online Handwritten Characters for Penmanship Learning Support System (TY, NM, MT), pp. 121–130.
HCIHCI-UA-2011-YangCS #analysis #learning #recognition
Facial Expression Recognition for Learning Status Analysis (MTY, YJC, YCS), pp. 131–138.
HCIHIMI-v2-2011-PohlML #hybrid #learning #standard
Transforming a Standard Lecture into a Hybrid Learning Scenario (HMP, JTM, JL), pp. 55–61.
HCIOCSC-2011-AhmadL #learning
Promoting Reflective Learning: The Role of Blogs in the Classroom (RA, WGL), pp. 3–11.
HCIOCSC-2011-PujariK #approach #machine learning #predict #recommendation
A Supervised Machine Learning Link Prediction Approach for Tag Recommendation (MP, RK), pp. 336–344.
HCIOCSC-2011-PuseyM #collaboration #design #learning #recommendation #wiki
Assessments in Large- and Small-Scale Wiki Collaborative Learning Environments: Recommendations for Educators and Wiki Designers (PP, GM), pp. 60–68.
AdaSIGAda-2011-Booch #ada
Everything i know i learned from ada (GB), pp. 17–18.
CAiSECAiSE-2011-DornD #process #self
Supporting Dynamic, People-Driven Processes through Self-learning of Message Flows (CD, SD), pp. 657–671.
ICEISICEIS-J-2011-Li11f #analysis #approach #case study #machine learning #type system #using
A Study on Noisy Typing Stream Analysis Using Machine Learning Approach (JL0), pp. 149–161.
ICEISICEIS-J-2011-NganBL11a #framework #learning #monitoring #multi #query
An Event-Based Service Framework for Learning, Querying and Monitoring Multivariate Time Series (CKN, AB, JL), pp. 208–223.
ICEISICEIS-v2-2011-NganBL #framework #learning #monitoring #multi #query
A Service Framework for Learning, Querying and Monitoring Multivariate Time Series (CKN, AB, JL), pp. 92–101.
ICEISICEIS-v4-2011-Marks #collaboration #learning #student
Students’ Acceptance of E-Group Collaboration Learning (AM), pp. 269–274.
CIKMCIKM-2011-ArguelloDC #learning #web
Learning to aggregate vertical results into web search results (JA, FD, JC), pp. 201–210.
CIKMCIKM-2011-CoffmanW #keyword #learning #rank #relational
Learning to rank results in relational keyword search (JC, ACW), pp. 1689–1698.
CIKMCIKM-2011-DhillonSS #information management #learning #modelling #multi #predict #web
Semi-supervised multi-task learning of structured prediction models for web information extraction (PSD, SS, SKS), pp. 957–966.
CIKMCIKM-2011-FeiJYLH #approach #behaviour #learning #multi #predict #social
Content based social behavior prediction: a multi-task learning approach (HF, RJ, YY, BL, JH), pp. 995–1000.
CIKMCIKM-2011-FuLZZ #learning #query
Do they belong to the same class: active learning by querying pairwise label homogeneity (YF, BL, XZ, CZ), pp. 2161–2164.
CIKMCIKM-2011-GiannopoulosBDS #learning #rank
Learning to rank user intent (GG, UB, TD, TKS), pp. 195–200.
CIKMCIKM-2011-KasiviswanathanMBS #detection #learning #taxonomy #topic #using
Emerging topic detection using dictionary learning (SPK, PM, AB, VS), pp. 745–754.
CIKMCIKM-2011-LauLBW #learning #scalability #sentiment #web
Leveraging web 2.0 data for scalable semi-supervised learning of domain-specific sentiment lexicons (RYKL, CLL, PB, KFW), pp. 2457–2460.
CIKMCIKM-2011-LiCHLJ #collaboration #learning #online
Collaborative online learning of user generated content (GL, KC, SCHH, WL, RJ), pp. 285–290.
CIKMCIKM-2011-LinC #data fusion #learning #query
Query sampling for learning data fusion (TCL, PJC), pp. 141–146.
CIKMCIKM-2011-LinLWX #learning #rank
Learning to rank with cross entropy (YL, HL, JW, KX), pp. 2057–2060.
CIKMCIKM-2011-LiSZ #feedback
Learning-based relevance feedback for web-based relation completion (ZL, LS, XZ), pp. 1535–1540.
CIKMCIKM-2011-LiuCZH #learning #random
Learning conditional random fields with latent sparse features for acronym expansion finding (JL, JC, YZ, YH), pp. 867–872.
CIKMCIKM-2011-LiuLH #bound #fault #kernel #learning
Learning kernels with upper bounds of leave-one-out error (YL, SL, YH), pp. 2205–2208.
CIKMCIKM-2011-NavigliFSLA #ambiguity #categorisation #learning #modelling #semantics #word
Two birds with one stone: learning semantic models for text categorization and word sense disambiguation (RN, SF, AS, OLdL, EA), pp. 2317–2320.
CIKMCIKM-2011-OroR #approach #learning #named
SILA: a spatial instance learning approach for deep webpages (EO, MR), pp. 2329–2332.
CIKMCIKM-2011-PandeyABHCRZ #behaviour #learning #what
Learning to target: what works for behavioral targeting (SP, MA, AB, AOH, PC, AR, MZ), pp. 1805–1814.
CIKMCIKM-2011-QianHCZN #ambiguity #machine learning
Combining machine learning and human judgment in author disambiguation (YnQ, YH, JC, QZ, ZN), pp. 1241–1246.
CIKMCIKM-2011-RamanJS #learning #ranking
Structured learning of two-level dynamic rankings (KR, TJ, PS), pp. 291–296.
CIKMCIKM-2011-SellamanickamGS #approach #learning #ranking
A pairwise ranking based approach to learning with positive and unlabeled examples (SS, PG, SKS), pp. 663–672.
CIKMCIKM-2011-SzummerY #learning #rank
Semi-supervised learning to rank with preference regularization (MS, EY), pp. 269–278.
CIKMCIKM-2011-TangLYSGGYZ #behaviour #learning #rank
Learning to rank audience for behavioral targeting in display ads (JT, NL, JY, YS, SG, BG, SY, MZ), pp. 605–610.
CIKMCIKM-2011-UllegaddiV #category theory #learning #query #rank #web
Learning to rank categories for web queries (PU, VV), pp. 2065–2068.
CIKMCIKM-2011-WangCWLWO #learning #similarity
Coupled nominal similarity in unsupervised learning (CW, LC, MW, JL, WW, YO), pp. 973–978.
CIKMCIKM-2011-WangHJT #categorisation #image #learning #metric #multi #performance
Efficient lp-norm multiple feature metric learning for image categorization (SW, QH, SJ, QT), pp. 2077–2080.
CIKMCIKM-2011-WangHLCH #learning #recommendation
Learning to recommend questions based on public interest (JW, XH, ZL, WHC, BH), pp. 2029–2032.
CIKMCIKM-2011-WangL #framework #learning #named #rank
CoRankBayes: bayesian learning to rank under the co-training framework and its application in keyphrase extraction (CW, SL), pp. 2241–2244.
CIKMCIKM-2011-YanGC #higher-order #learning #query #recommendation
Context-aware query recommendation by learning high-order relation in query logs (XY, JG, XC), pp. 2073–2076.
CIKMCIKM-2011-YangZKL #how #learning #question #why
Can irrelevant data help semi-supervised learning, why and how? (HY, SZ, IK, MRL), pp. 937–946.
CIKMCIKM-2011-YanTLSL #learning #predict
Citation count prediction: learning to estimate future citations for literature (RY, JT, XL, DS, XL), pp. 1247–1252.
CIKMCIKM-2011-ZhangYCT #detection
A machine-learned proactive moderation system for auction fraud detection (LZ, JY, WC, BLT), pp. 2501–2504.
CIKMCIKM-2011-ZhaoYX #independence #information management #learning #web
Max margin learning on domain-independent web information extraction (BZ, XY, EPX), pp. 1305–1310.
CIKMCIKM-2011-ZhuZYGX #learning
Transfer active learning (ZZ, XZ, YY, YFG, XX), pp. 2169–2172.
ECIRECIR-2011-BuffoniTG #ranking
The Importance of the Depth for Text-Image Selection Strategy in Learning-To-Rank (DB, ST, PG), pp. 743–746.
ECIRECIR-2011-HofmannWR #learning #online #rank
Balancing Exploration and Exploitation in Learning to Rank Online (KH, SW, MdR), pp. 251–263.
ECIRECIR-2011-LeonardLZTCD #data fusion #information retrieval #machine learning #metric
Applying Machine Learning Diversity Metrics to Data Fusion in Information Retrieval (DL, DL, LZ, FT, RWC, JD), pp. 695–698.
ECIRECIR-2011-MacdonaldO #learning #modelling #ranking
Learning Models for Ranking Aggregates (CM, IO), pp. 517–529.
ECIRECIR-2011-ZhouH #comprehension #learning #natural language #random
Learning Conditional Random Fields from Unaligned Data for Natural Language Understanding (DZ, YH), pp. 283–288.
ICMLICML-2011-BabenkoVDB #learning #multi
Multiple Instance Learning with Manifold Bags (BB, NV, PD, SB), pp. 81–88.
ICMLICML-2011-BabesMLS #learning #multi
Apprenticeship Learning About Multiple Intentions (MB, VNM, KS, MLL), pp. 897–904.
ICMLICML-2011-BazzaniFLMT #learning #network #policy #recognition #video
Learning attentional policies for tracking and recognition in video with deep networks (LB, NdF, HL, VM, JAT), pp. 937–944.
ICMLICML-2011-BuffoniCGU #learning #standard
Learning Scoring Functions with Order-Preserving Losses and Standardized Supervision (DB, CC, PG, NU), pp. 825–832.
ICMLICML-2011-Bylander #learning #linear #multi #polynomial
Learning Linear Functions with Quadratic and Linear Multiplicative Updates (TB), pp. 505–512.
ICMLICML-2011-ChakrabortyS #learning
Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function’s In-Degree (DC, PS), pp. 737–744.
ICMLICML-2011-ChenPSDC #analysis #learning #process
The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning (BC, GP, GS, DBD, LC), pp. 361–368.
ICMLICML-2011-ChoRI #adaptation #learning #strict
Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines (KC, TR, AI), pp. 105–112.
ICMLICML-2011-DauphinGB #learning #re-engineering #scalability
Large-Scale Learning of Embeddings with Reconstruction Sampling (YD, XG, YB), pp. 945–952.
ICMLICML-2011-DinuzzoOGP #coordination #kernel #learning
Learning Output Kernels with Block Coordinate Descent (FD, CSO, PVG, GP), pp. 49–56.
ICMLICML-2011-DudikLL #evaluation #learning #policy #robust
Doubly Robust Policy Evaluation and Learning (MD, JL, LL), pp. 1097–1104.
ICMLICML-2011-GlorotBB #adaptation #approach #classification #learning #scalability #sentiment
Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach (XG, AB, YB), pp. 513–520.
ICMLICML-2011-Gould #learning #linear #markov #random
Max-margin Learning for Lower Linear Envelope Potentials in Binary Markov Random Fields (SG), pp. 193–200.
ICMLICML-2011-GuilloryB #learning
Simultaneous Learning and Covering with Adversarial Noise (AG, JAB), pp. 369–376.
ICMLICML-2011-HarelM #learning #multi
Learning from Multiple Outlooks (MH, SM), pp. 401–408.
ICMLICML-2011-HeL #framework #learning #multi
A Graphbased Framework for Multi-Task Multi-View Learning (JH, RL), pp. 25–32.
ICMLICML-2011-HuWC #coordination #kernel #learning #named #parametricity #scalability #using
BCDNPKL: Scalable Non-Parametric Kernel Learning Using Block Coordinate Descent (EH, BW, SC), pp. 209–216.
ICMLICML-2011-JawanpuriaNR #kernel #learning #performance #using
Efficient Rule Ensemble Learning using Hierarchical Kernels (PJ, JSN, GR), pp. 161–168.
ICMLICML-2011-KangGS #learning #multi
Learning with Whom to Share in Multi-task Feature Learning (ZK, KG, FS), pp. 521–528.
ICMLICML-2011-KuwadekarN #classification #learning #modelling #relational
Relational Active Learning for Joint Collective Classification Models (AK, JN), pp. 385–392.
ICMLICML-2011-LeeW #identification #learning #online #probability
Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning (SL, SJW), pp. 1121–1128.
ICMLICML-2011-LeNCLPN #learning #on the #optimisation
On optimization methods for deep learning (QVL, JN, AC, AL, BP, AYN), pp. 265–272.
ICMLICML-2011-LiZSC #integration #learning #modelling #on the #taxonomy #topic
On the Integration of Topic Modeling and Dictionary Learning (LL, MZ, GS, LC), pp. 625–632.
ICMLICML-2011-LuB #learning #modelling
Learning Mallows Models with Pairwise Preferences (TL, CB), pp. 145–152.
ICMLICML-2011-Maaten #kernel #learning
Learning Discriminative Fisher Kernels (LvdM), pp. 217–224.
ICMLICML-2011-MachartPARG #kernel #learning #probability #rank
Stochastic Low-Rank Kern