BibSLEIGH — learn stem

Used together with:

base (503)
use (452)
model (328)
machin (311)
system (286)

Stem learn$ (all stems)

4419 papers:

ECSA-2015-KiwelekarW #architecture #learning: Learning Objectives for a Course on Software Architecture (AWK, HSW), pp. 169–180.
CASE-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.
CASE-2015-FarhanPWL #algorithm #machine learning #predict #using: Predicting individual thermal comfort using machine learning algorithms (AAF, KRP, BW, PBL), pp. 708–713.
CASE-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.
CASE-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.
CASE-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.
CASE-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.
CASE-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.
CASE-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.
CASE-2015-WatteyneAV #lessons learnt #scalability: Lessons learned from large-scale dense IEEE802.15.4 connectivity traces (TW, CA, XV), pp. 145–150.
CASE-2015-ZhangWZZ #automaton #learning #optimisation #performance: Incorporation of ordinal optimization into learning automata for high learning efficiency (JZ, CW, DZ, MZ), pp. 1206–1211.
DAC-2015-SztipanovitsBNK #cyber-physical #design #lessons learnt: Design tool chain for cyber-physical systems: lessons learned (JS, TB, SN, XDK, EKJ), p. 6.
DAC-2015-VenkataramaniRL #classification #energy #machine learning: Scalable-effort classifiers for energy-efficient machine learning (SV, AR, JL, MS), p. 6.
DATE-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.
DATE-2015-ChenM #distributed #learning #manycore #optimisation #performance: Distributed reinforcement learning for power limited many-core system performance optimization (ZC, DM), pp. 1521–1526.
DATE-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.
DATE-2015-RenTB #detection #learning #statistics: Detection of illegitimate access to JTAG via statistical learning in chip (XR, VGT, RD(B), pp. 109–114.
DATE-2015-ZhuM #linear #machine learning #optimisation #programming #using: Optimizing dynamic trace signal selection using machine learning and linear programming (CSZ, SM), pp. 1289–1292.
DocEng-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.
DocEng-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.
DRR-2015-FuLLQT #diagrams #learning #multi #retrieval: A diagram retrieval method with multi-label learning (SF, XL, LL, JQ, ZT).
HT-2015-KirchnerR #collaboration #in the cloud #learning: Collaborative Learning in the Cloud: A Cross-Cultural Perspective of Collaboration (KK, LR), pp. 333–336.
HT-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.
SIGMOD-2015-HuangBTRTR #machine learning #scalability: Resource Elasticity for Large-Scale Machine Learning (BH, MB, YT, BR, ST, FRR), pp. 137–152.
SIGMOD-2015-KumarNP #learning #linear #modelling #normalisation: Learning Generalized Linear Models Over Normalized Data (AK, JFN, JMP), pp. 1969–1984.
SIGMOD-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.
VLDB-2015-KumarJYNP #machine learning #normalisation #optimisation: Demonstration of Santoku: Optimizing Machine Learning over Normalized Data (AK, MJ, BY, JFN, JMP), pp. 1864–1875.
VLDB-2015-QianGJ #adaptation #comparison #learning: Learning User Preferences By Adaptive Pairwise Comparison (LQ, JG, HVJ), pp. 1322–1333.
ITiCSE-2015-AlshammariAH #adaptation #education #learning #security: The Impact of Learning Style Adaptivity in Teaching Computer Security (MA, RA, RJH), pp. 135–140.
ITiCSE-2015-AndersonNM #programming: Facilitating Programming Success in Data Science Courses through Gamified Scaffolding and Learn2Mine (PEA, TN, RAM), pp. 99–104.
ITiCSE-2015-Annamaa #ide #learning #programming #python: Thonny, : a Python IDE for Learning Programming (AA), p. 343.
ITiCSE-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.
ITiCSE-2015-Hamilton #education #learning: Learning and Teaching Computing Sustainability (MH), p. 338.
ITiCSE-2015-Harms #community #learning #source code: Department Programs to Encourage and Support Service Learning and Community Engagement (DEH), p. 330.
ITiCSE-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.
ITiCSE-2015-ParreiraPC #c #named #student: PCRS-C: Helping Students Learn C (DMP, AP, MC), p. 347.
ITiCSE-2015-QuinsonO #education #learning #programming: A Teaching System to Learn Programming: the Programmer’s Learning Machine (MQ, GO), pp. 260–265.
ITiCSE-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.
ITiCSE-2015-SettleLS #community #learning: A Computer Science Linked-courses Learning Community (AS, JL, TS), pp. 123–128.
ITiCSE-2015-TarmazdiVSFF #learning #using #visualisation: Using Learning Analytics to Visualise Computer Science Teamwork (HT, RV, CS, KEF, NJGF), pp. 165–170.
ITiCSE-2015-Tudor #learning #optimisation #query #xml: Virtual Learning Laboratory about Query Optimization against XML Data (LNT), p. 348.
ICSME-2015-CorleyDK #feature model #learning: Exploring the use of deep learning for feature location (CSC, KD, NAK), pp. 556–560.
ICSME-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.
MSR-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.
MSR-2015-WhiteVVP #learning #repository #towards: Toward Deep Learning Software Repositories (MW, CV, MLV, DP), pp. 334–345.
STOC-2015-BarakKS #composition #learning #taxonomy: Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method (BB, JAK, DS), pp. 143–151.
STOC-2015-Bresler #graph #learning #modelling: Efficiently Learning Ising Models on Arbitrary Graphs (GB), pp. 771–782.
STOC-2015-GeHK #learning: Learning Mixtures of Gaussians in High Dimensions (RG, QH, SMK), pp. 761–770.
STOC-2015-HardtP #bound #learning: Tight Bounds for Learning a Mixture of Two Gaussians (MH, EP), pp. 753–760.
STOC-2015-LiRSS #learning #statistics: Learning Arbitrary Statistical Mixtures of Discrete Distributions (JL, YR, LJS, CS), pp. 743–752.
LATA-2015-Yoshinaka #boolean grammar #grammar inference #learning: Learning Conjunctive Grammars and Contextual Binary Feature Grammars (RY), pp. 623–635.
FM-2015-Damm #analysis #automation #lessons learnt #named #verification: AVACS: Automatic Verification and Analysis of Complex Systems Highlights and Lessons Learned (WD), pp. 18–19.
SEFM-2015-Muhlberg0DLP #learning #source code #verification: Learning Assertions to Verify Linked-List Programs (JTM, DHW, MD, GL, FP), pp. 37–52.
ICFP-2015-ZhuNJ #learning #refinement: Learning refinement types (HZ, AVN, SJ), pp. 400–411.
CHI-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.
CHI-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.
CHI-2015-CaiGGM #education #named: Wait-Learning: Leveraging Wait Time for Second Language Education (CJC, PJG, JRG, RCM), pp. 3701–3710.
CHI-2015-DavisK #learning #student: Investigating High School Students’ Perceptions of Digital Badges in Afterschool Learning (KD, EK), pp. 4043–4046.
CHI-2015-KardanC #adaptation #evaluation #interactive #learning #simulation: Providing Adaptive Support in an Interactive Simulation for Learning: An Experimental Evaluation (SK, CC), pp. 3671–3680.
CHI-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.
CHI-2015-Noble #learning #self: Resilience Ex Machina: Learning a Complex Medical Device for Haemodialysis Self-Treatment (PJN), pp. 4147–4150.
CHI-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.
CHI-2015-ShovmanBSS #3d #interface #learning: Twist and Learn: Interface Learning in 3DOF Exploration of 3D Scatterplots (MMS, JLB, AS, KCSB), pp. 313–316.
CHI-2015-StrohmayerCB #learning #people: Exploring Learning Ecologies among People Experiencing Homelessness (AS, RC, MB), pp. 2275–2284.
CHI-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.
CHI-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.
CSCW-2015-Anya #design #exclamation #question #what: Bridge the Gap!: What Can Work Design in Crowdwork Learn from Work Design Theories? (OA), pp. 612–627.
CSCW-2015-ChengB #classification #hybrid #machine learning #named: Flock: Hybrid Crowd-Machine Learning Classifiers (JC, MSB), pp. 600–611.
CSCW-2015-CoetzeeLFHH #interactive #learning #scalability: Structuring Interactions for Large-Scale Synchronous Peer Learning (DC, SL, AF, BH, MAH), pp. 1139–1152.
CSCW-2015-DornSS #collaboration #learning: Piloting TrACE: Exploring Spatiotemporal Anchored Collaboration in Asynchronous Learning (BD, LBS, AS), pp. 393–403.
CSCW-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.
DHM-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.
DHM-HM-2015-NishimuraK #case study #learning: A Study on Learning Effects of Marking with Highlighter Pen (HN, NK), pp. 357–367.
DUXU-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.
DUXU-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.
DUXU-DD-2015-Schneidermeier #lessons learnt #usability: Lessons Learned in Usability Consulting (TS), pp. 247–255.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
HCI-DE-2015-BakkeB #developer #learning #proximity: The Closer the Better: Effects of Developer-User Proximity for Mutual Learning (SB, TB), pp. 14–26.
HCI-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.
HIMI-IKC-2015-AraiTA #development #learning: Development of a Learning Support System for Class Structure Mapping Based on Viewpoint (TA, TT, TA), pp. 285–293.
HIMI-IKC-2015-HasegawaD #approach #framework #learning #ubiquitous: A Ubiquitous Lecture Archive Learning Platform with Note-Centered Approach (SH, JD), pp. 294–303.
HIMI-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.
HIMI-IKC-2015-Iwata #difference #learning: Method to Generate an Operation Learning Support System by Shortcut Key Differences in Similar Software (HI), pp. 332–340.
HIMI-IKC-2015-KimitaMMNIS #education #learning: Learning State Model for Value Co-Creative Education Services (KK, KM, SM, YN, TI, YS), pp. 341–349.
HIMI-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.
HIMI-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.
HIMI-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.
LCT-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.
LCT-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.
LCT-2015-DirinN #design #development #framework: Assessments of User Centered Design Framework for M-learning Application Development (AD, MN), pp. 62–74.
LCT-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.
LCT-2015-FardounAC #education #evaluation: Creation of Meaningful-Learning and Continuous Evaluation Education System (HMF, AA, APC), pp. 218–226.
LCT-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.
LCT-2015-FonsecaRVG #3d #education #learning: From Formal to Informal 3D Learning. Assesment of Users in the Education (DF, ER, FV, ODG), pp. 460–469.
LCT-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.
LCT-2015-GonzalezHGS #interactive #learning #student #tool support: Exploring Student Interactions: Learning Analytics Tools for Student Tracking (MÁCG, ÁHG, FJGP, MLSE), pp. 50–61.
LCT-2015-HoffmannPLSMJ #learning #student: Enhancing the Learning Success of Engineering Students by Virtual Experiments (MH, LP, LL, KS, TM, SJ), pp. 394–405.
LCT-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.
LCT-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.
LCT-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.
LCT-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.
LCT-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.
LCT-2015-OrehovackiB #game studies #learning #programming #quality: Inspecting Quality of Games Designed for Learning Programming (TO, SB), pp. 620–631.
LCT-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.
LCT-2015-ShimizuO #design #implementation #learning #novel #word: Design and Implementation of Novel Word Learning System “Überall” (RS, KO), pp. 148–159.
LCT-2015-TamuraTHN #generative #learning #wiki: Generating Quizzes for History Learning Based on Wikipedia Articles (YT, YT, YH, YIN), pp. 337–346.
LCT-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.
LCT-2015-VielRTP #design #interactive #learning #multi: Design Solutions for Interactive Multi-video Multimedia Learning Objects (CCV, KRHR, CACT, MdGCP), pp. 160–171.
LCT-2015-YusoffK #design #game studies #interactive #learning #persuasion: Game Rhetoric: Interaction Design Model of Persuasive Learning for Serious Games (ZY, AK), pp. 644–654.
ICEIS-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.
ICEIS-v1-2015-RibeiroTWBE #learning: A Learning Model for Intelligent Agents Applied to Poultry Farming (RR, MT, ALW, APB, FE), pp. 495–503.
ICEIS-v1-2015-SouzaBGBE #learning #online: Applying Ensemble-based Online Learning Techniques on Crime Forecasting (AJdS, APB, HMG, JPB, FE), pp. 17–24.
ICEIS-v2-2015-Judrups #analysis #information management #integration: Analysis of Knowledge Management and E-Learning Integration Approaches (JJ), pp. 451–456.
ECIR-2015-HuynhHR #analysis #learning #sentiment #strict: Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis (TH, YH, SMR), pp. 447–452.
ECIR-2015-KingI #clustering #generative #music: Generating Music Playlists with Hierarchical Clustering and Q-Learning (JK, VI), pp. 315–326.
ECIR-2015-LiHLZ #twitter: Selecting Training Data for Learning-Based Twitter Search (DL, BH, TL, XZ), pp. 501–506.
ECIR-2015-NicosiaBM #learning #rank: Learning to Rank Aggregated Answers for Crossword Puzzles (MN, GB, AM), pp. 556–561.
ECIR-2015-PasinatoMZ #elicitation #learning #rating: Active Learning Applied to Rating Elicitation for Incentive Purposes (MBP, CEM, GZ), pp. 291–302.
ECIR-2015-PelejaM #learning #retrieval #sentiment: Learning Sentiment Based Ranked-Lexicons for Opinion Retrieval (FP, JM), pp. 435–440.
ICML-2015-AmidU #learning #multi: Multiview Triplet Embedding: Learning Attributes in Multiple Maps (EA, AU), pp. 1472–1480.
ICML-2015-BachHBG #learning #performance: Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs (SHB, BH, JLBG, LG), pp. 381–390.
ICML-2015-BlumH #contest #machine learning #reliability: The Ladder: A Reliable Leaderboard for Machine Learning Competitions (AB, MH), pp. 1006–1014.
ICML-2015-Bou-AmmarTE #learning #policy #sublinear: Safe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret (HBA, RT, EE), pp. 2361–2369.
ICML-2015-ChangKADL #education #learning: Learning to Search Better than Your Teacher (KWC, AK, AA, HDI, JL), pp. 2058–2066.
ICML-2015-ChenSYU #learning #modelling: Learning Deep Structured Models (LCC, AGS, ALY, RU), pp. 1785–1794.
ICML-2015-CilibertoMPR #learning #multi: Convex Learning of Multiple Tasks and their Structure (CC, YM, TAP, LR), pp. 1548–1557.
ICML-2015-CohenH #learning #online: Following the Perturbed Leader for Online Structured Learning (AC, TH), pp. 1034–1042.
ICML-2015-DanielyGS #adaptation #learning #online: Strongly Adaptive Online Learning (AD, AG, SSS), pp. 1405–1411.
ICML-2015-FetayaU #invariant #learning: Learning Local Invariant Mahalanobis Distances (EF, SU), pp. 162–168.
ICML-2015-GarberHM #learning #online: Online Learning of Eigenvectors (DG, EH, TM), pp. 560–568.
ICML-2015-GuptaAGN #learning #precise: Deep Learning with Limited Numerical Precision (SG, AA, KG, PN), pp. 1737–1746.
ICML-2015-HallakSMM #learning #modelling: Off-policy Model-based Learning under Unknown Factored Dynamics (AH, FS, TAM, SM), pp. 711–719.
ICML-2015-Hernandez-Lobato15b #learning #network #probability #scalability: Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks (JMHL, RA), pp. 1861–1869.
ICML-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.
ICML-2015-HongYKH #learning #network #online: Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network (SH, TY, SK, BH), pp. 597–606.
ICML-2015-HsiehND #learning #matrix: PU Learning for Matrix Completion (CJH, NN, ISD), pp. 2445–2453.
ICML-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.
ICML-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.
ICML-2015-JiangKS #abstraction #learning #modelling: Abstraction Selection in Model-based Reinforcement Learning (NJ, AK, SS), pp. 179–188.
ICML-2015-Kandemir #learning #process #symmetry: Asymmetric Transfer Learning with Deep Gaussian Processes (MK), pp. 730–738.
ICML-2015-KvetonSWA #learning #rank: Cascading Bandits: Learning to Rank in the Cascade Model (BK, CS, ZW, AA), pp. 767–776.
ICML-2015-LakshmananOR #bound #learning: Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning (KL, RO, DR), pp. 524–532.
ICML-2015-LeC #learning #metric #using: Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations (TL, MC), pp. 2002–2011.
ICML-2015-LiuY #graph #learning #predict: Bipartite Edge Prediction via Transductive Learning over Product Graphs (HL, YY), pp. 1880–1888.
ICML-2015-LondonHG #approximate #learning: The Benefits of Learning with Strongly Convex Approximate Inference (BL, BH, LG), pp. 410–418.
ICML-2015-LongC0J #adaptation #learning #network: Learning Transferable Features with Deep Adaptation Networks (ML, YC, JW, MJ), pp. 97–105.
ICML-2015-Lopez-PazMST #learning #towards: Towards a Learning Theory of Cause-Effect Inference (DLP, KM, BS, IT), pp. 1452–1461.
ICML-2015-MaclaurinDA #learning #optimisation: Gradient-based Hyperparameter Optimization through Reversible Learning (DM, DKD, RPA), pp. 2113–2122.
ICML-2015-MarietS #algorithm #fixpoint #learning #process: Fixed-point algorithms for learning determinantal point processes (ZM, SS), pp. 2389–2397.
ICML-2015-MenonROW #estimation #learning: Learning from Corrupted Binary Labels via Class-Probability Estimation (AKM, BvR, CSO, BW), pp. 125–134.
ICML-2015-PerrotH #analysis #learning #metric: A Theoretical Analysis of Metric Hypothesis Transfer Learning (MP, AH), pp. 1708–1717.
ICML-2015-PhamRFA #learning #multi #novel: Multi-instance multi-label learning in the presence of novel class instances (ATP, RR, XZF, JPA), pp. 2427–2435.
ICML-2015-PiechHNPSG #feedback #learning #student: Learning Program Embeddings to Propagate Feedback on Student Code (CP, JH, AN, MP, MS, LJG), pp. 1093–1102.
ICML-2015-PlessisNS #learning: Convex Formulation for Learning from Positive and Unlabeled Data (MCdP, GN, MS), pp. 1386–1394.
ICML-2015-Romera-ParedesT #approach #learning: An embarrassingly simple approach to zero-shot learning (BRP, PHST), pp. 2152–2161.
ICML-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.
ICML-2015-SibonyCJ #learning #ranking #statistics: MRA-based Statistical Learning from Incomplete Rankings (ES, SC, JJ), pp. 1432–1441.
ICML-2015-Sohl-DicksteinW #learning #using: Deep Unsupervised Learning using Nonequilibrium Thermodynamics (JSD, EAW, NM, SG), pp. 2256–2265.
ICML-2015-SrivastavaMS #learning #using #video: Unsupervised Learning of Video Representations using LSTMs (NS, EM, RS), pp. 843–852.
ICML-2015-SteinhardtL15a #learning #modelling #predict: Learning Fast-Mixing Models for Structured Prediction (JS, PL), pp. 1063–1072.
ICML-2015-SwaminathanJ #feedback #learning: Counterfactual Risk Minimization: Learning from Logged Bandit Feedback (AS, TJ), pp. 814–823.
ICML-2015-TangSX #learning #network: Learning Scale-Free Networks by Dynamic Node Specific Degree Prior (QT, SS, JX), pp. 2247–2255.
ICML-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.
ICML-2015-VanseijenS #learning: A Deeper Look at Planning as Learning from Replay (HV, RS), pp. 2314–2322.
ICML-2015-WangALB #learning #multi #on the #representation: On Deep Multi-View Representation Learning (WW, RA, KL, JAB), pp. 1083–1092.
ICML-2015-WangWLCW #learning #multi #segmentation: Multi-Task Learning for Subspace Segmentation (YW, DPW, QL, WC, IJW), pp. 1209–1217.
ICML-2015-WangY #learning #matrix #multi: Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices (JW, JY), pp. 1747–1756.
ICML-2015-WeiIB #learning #set: Submodularity in Data Subset Selection and Active Learning (KW, RKI, JAB), pp. 1954–1963.
ICML-2015-WeissN #alias #learning: Learning Parametric-Output HMMs with Two Aliased States (RW, BN), pp. 635–644.
ICML-2015-WenKA #combinator #learning #performance #scalability: Efficient Learning in Large-Scale Combinatorial Semi-Bandits (ZW, BK, AA), pp. 1113–1122.
ICML-2015-WuS #algorithm #learning #modelling #online: An Online Learning Algorithm for Bilinear Models (YW, SS), pp. 890–898.
ICML-2015-YogatamaFDS #learning #word: Learning Word Representations with Hierarchical Sparse Coding (DY, MF, CD, NAS), pp. 87–96.
ICML-2015-YuB #learning: Learning Submodular Losses with the Lovasz Hinge (JY, MBB), pp. 1623–1631.
ICML-2015-YuCL #learning #multi #online #rank: Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams (RY, DC, YL), pp. 238–247.
KDD-2015-Agarwal #machine learning #scalability #statistics #web: Scaling Machine Learning and Statistics for Web Applications (DA), p. 1621.
KDD-2015-Athey #evaluation #machine learning #policy: Machine Learning and Causal Inference for Policy Evaluation (SA), pp. 5–6.
KDD-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.
KDD-2015-Durrant-Whyte #machine learning: Data, Knowledge and Discovery: Machine Learning meets Natural Science (HDW), p. 7.
KDD-2015-DuS #adaptation #feature model #learning: Unsupervised Feature Selection with Adaptive Structure Learning (LD, YDS), pp. 209–218.
KDD-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.
KDD-2015-GleichM #algorithm #graph #learning #using: Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms (DFG, MWM), pp. 359–368.
KDD-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.
KDD-2015-HanZ #learning #multi: Learning Tree Structure in Multi-Task Learning (LH, YZ), pp. 397–406.
KDD-2015-JohanssonD #geometry #graph #learning #similarity #using: Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings (FDJ, DPD), pp. 467–476.
KDD-2015-Koller #named #question #what: MOOCS: What Have We Learned? (DK), p. 3.
KDD-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.
KDD-2015-LanH #complexity #learning #multi: Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning (CL, JH), pp. 627–634.
KDD-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.
KDD-2015-MaoWGS #graph #learning #reduction: Dimensionality Reduction Via Graph Structure Learning (QM, LW, SG, YS), pp. 765–774.
KDD-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.
KDD-2015-Papagiannopoulou #learning #multi: Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning (CP, GT, IT), pp. 915–924.
KDD-2015-Pratt #machine learning #predict #protocol #proving: Proof Protocol for a Machine Learning Technique Making Longitudinal Predictions in Dynamic Contexts (KBP), pp. 2049–2058.
KDD-2015-RiondatoU15a #algorithm #learning #statistics: VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms (MR, EU), pp. 2321–2322.
KDD-2015-Schleier-Smith #agile #architecture #machine learning #realtime: An Architecture for Agile Machine Learning in Real-Time Applications (JSS), pp. 2059–2068.
KDD-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.
KDD-2015-ShashidharPA #machine learning: Spoken English Grading: Machine Learning with Crowd Intelligence (VS, NP, VA), pp. 2089–2097.
KDD-2015-SunAYMMBY #classification #learning: Transfer Learning for Bilingual Content Classification (QS, MSA, BY, CM, VM, AB, JY), pp. 2147–2156.
KDD-2015-TanSZ0 #learning #transitive: Transitive Transfer Learning (BT, YS, EZ, QY), pp. 1155–1164.
KDD-2015-VeeriahDQ #architecture #learning #predict: Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction (VV, RD, GJQ), pp. 1205–1214.
KDD-2015-WangWY #collaboration #learning #recommendation: Collaborative Deep Learning for Recommender Systems (HW, NW, DYY), pp. 1235–1244.
KDD-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.
KDD-2015-XuSB #learning #predict: Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction (TX, JS, JB), pp. 1345–1354.
KDD-2015-YangH #learning #multi: Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning (PY, JH), pp. 1375–1384.
KDD-2015-YangSJWDY #learning #visual notation: Structural Graphical Lasso for Learning Mouse Brain Connectivity (SY, QS, SJ, PW, ID, JY), pp. 1385–1394.
KDD-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.
KDD-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.
KDD-2015-ZhaoSYCLR #learning #multi: Multi-Task Learning for Spatio-Temporal Event Forecasting (LZ, QS, JY, FC, CTL, NR), pp. 1503–1512.
MLDM-2015-Chou #data-driven #geometry #learning: Data Driven Geometry for Learning (EPC), pp. 395–402.
MLDM-2015-DhulekarNOY #graph #learning #mining #predict: Seizure Prediction by Graph Mining, Transfer Learning, and Transformation Learning (ND, SN, BO, BY), pp. 32–52.
MLDM-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.
MLDM-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.
MLDM-2015-KrasotkinaM #approach #optimisation #ranking: A Bayesian Approach to Sparse Learning-to-Rank for Search Engine Optimization (OK, VM), pp. 382–394.
MLDM-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.
RecSys-2015-AlmahairiKCC #collaboration #distributed #learning: Learning Distributed Representations from Reviews for Collaborative Filtering (AA, KK, KC, ACC), pp. 147–154.
RecSys-2015-HuD #machine learning #recommendation #scalability: Scalable Recommender Systems: Where Machine Learning Meets Search (SYDH, JD), pp. 365–366.
RecSys-2015-SongCL #incremental #matrix #recommendation: Incremental Matrix Factorization via Feature Space Re-learning for Recommender System (QS, JC, HL), pp. 277–280.
SEKE-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.
SEKE-2015-GoswamiWS #learning #performance #using: Using Learning Styles of Software Professionals to Improve their Inspection Team Performance (AG, GSW, AS), pp. 680–685.
SEKE-2015-LiuXC #learning #recommendation: Context-aware Recommendation System with Anonymous User Profile Learning (YL, YX, MC), pp. 93–98.
SEKE-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.
SEKE-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.
SEKE-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.
SEKE-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.
SEKE-2015-WanderleyP #detection #folksonomy #learning: Learning Folksonomies for Trend Detection in Task-Oriented Dialogues (GW, ECP), pp. 483–488.
SEKE-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.
SIGIR-2015-Arora #learning: Promoting User Engagement and Learning in Amorphous Search Tasks (PA), p. 1051.
SIGIR-2015-CormackG #bibliography #learning #multi #perspective: Multi-Faceted Recall of Continuous Active Learning for Technology-Assisted Review (GVC, MRG), pp. 763–766.
SIGIR-2015-FoleyBJ #learning #web: Learning to Extract Local Events from the Web (JF, MB, VJ), pp. 423–432.
SIGIR-2015-HarveyHE #learning #query: Learning by Example: Training Users with High-quality Query Suggestions (MH, CH, DE), pp. 133–142.
SIGIR-2015-Li15a #information retrieval #learning: Transfer Learning for Information Retrieval (PL), p. 1061.
SIGIR-2015-LiuW #collaboration #learning: Learning Context-aware Latent Representations for Context-aware Collaborative Filtering (XL, WW), pp. 887–890.
SIGIR-2015-MehrotraY #learning #query #rank #using: Representative & Informative Query Selection for Learning to Rank using Submodular Functions (RM, EY), pp. 545–554.
SIGIR-2015-SeverynM #learning #network #rank: Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks (AS, AM), pp. 373–382.
SIGIR-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.
SIGIR-2015-SpinaPR #learning #microblog: Active Learning for Entity Filtering in Microblog Streams (DS, MHP, MdR), pp. 975–978.
SIGIR-2015-WangGLXWC #learning #recommendation #representation: Learning Hierarchical Representation Model for NextBasket Recommendation (PW, JG, YL, JX, SW, XC), pp. 403–412.
SIGIR-2015-WangLWZZ #learning #named: LBMCH: Learning Bridging Mapping for Cross-modal Hashing (YW, XL, LW, WZ, QZ), pp. 999–1002.
SIGIR-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.
SIGIR-2015-ZamaniMS #adaptation #evaluation #learning #multi: Adaptive User Engagement Evaluation via Multi-task Learning (HZ, PM, AS), pp. 1011–1014.
SIGIR-2015-ZhengC #distributed #learning: Learning to Reweight Terms with Distributed Representations (GZ, JC), pp. 575–584.
MoDELS-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.
MoDELS-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.
OOPSLA-2015-OhYY #adaptation #learning #optimisation #program analysis: Learning a strategy for adapting a program analysis via bayesian optimisation (HO, HY, KY), pp. 572–588.
SAC-2015-BarrosCMP #education #learning #repository #reuse: Integrating educational repositories to improve the reuse of learning objects (HB, EC, JM, RP), pp. 270–272.
SAC-2015-Brefeld #learning #multi: Multi-view learning with dependent views (UB), pp. 865–870.
SAC-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.
SAC-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.
SAC-2015-GomesBE #classification #data type #learning: Pairwise combination of classifiers for ensemble learning on data streams (HMG, JPB, FE), pp. 941–946.
SAC-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.
SAC-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.
SAC-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.
SAC-2015-OmatuYI #classification #learning #smell: Smell classification of wines by the learning vector quantization method (SO, MY, YI), pp. 195–200.
SAC-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.
SAC-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.
SAC-2015-Pesare #learning #social: Smart learning environments for social learning (EP), pp. 273–274.
SAC-2015-ReadPB #data type #learning: Deep learning in partially-labeled data streams (JR, FPC, AB), pp. 954–959.
SAC-2015-ReddySC #approach #aspect-oriented #incremental #learning #performance #weaving: Incremental aspect weaving: an approach for faster AOP learning (YRR, AS, MC), pp. 1480–1485.
SAC-2015-RegoMP #approach #detection #folksonomy #learning: A supervised learning approach to detect subsumption relations between tags in folksonomies (ASdCR, LBM, CESP), pp. 409–415.
SAC-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.
SAC-2015-SugiyamaS #learning #multi: Meta-strategy for cooperative tasks with learning of environments in multi-agent continuous tasks (AS, TS), pp. 494–500.
SAC-2015-WanderleyP #folksonomy #learning: Learning folksonomies from task-oriented dialogues (GMPW, ECP), pp. 360–367.
ESEC-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-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-FSE-2015-SunXLLQ #abstraction #learning #named #testing #validation: TLV: abstraction through testing, learning, and validation (JS, HX, YL, SWL, SQ), pp. 698–709.
ICSE-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.
ICSE-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.
ICSE-v1-2015-ZhuHFZLZ #developer #learning: Learning to Log: Helping Developers Make Informed Logging Decisions (JZ, PH, QF, HZ, MRL, DZ), pp. 415–425.
ICSE-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.
ICSE-v2-2015-Honsel #evolution #learning #mining #simulation #statistics: Statistical Learning and Software Mining for Agent Based Simulation of Software Evolution (VH), pp. 863–866.
ICSE-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.
ICSE-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.
ICSE-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.
ICSE-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.
ICSE-v2-2015-SedelmaierL #education #induction #learning #re-engineering: Active and Inductive Learning in Software Engineering Education (YS, DL), pp. 418–427.
ICSE-v2-2015-SoundarajanJR #collaboration #re-engineering: Collaborative and Cooperative-Learning in Software Engineering Courses (NS, SJ, RR), pp. 319–322.
ICSE-v2-2015-WilkinsG #design #learning #student: Drawing Insight from Student Perceptions of Reflective Design Learning (TVW, JCG), pp. 253–262.
ASPLOS-2015-LiuCLZZTFZC #machine learning #named: PuDianNao: A Polyvalent Machine Learning Accelerator (DFL, TC, SL, JZ, SZ, OT, XF, XZ, YC), pp. 369–381.
CGO-2015-McAfeeO #framework #generative #learning #multi #named: EMEURO: a framework for generating multi-purpose accelerators via deep learning (LCM, KO), pp. 125–135.
HPCA-2015-WuGLJC #estimation #machine learning #performance #using: GPGPU performance and power estimation using machine learning (GYW, JLG, AL, NJ, DC), pp. 564–576.
PPoPP-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.
CAV-2015-BrazdilCCFK #learning #markov #process: Counterexample Explanation by Learning Small Strategies in Markov Decision Processes (TB, KC, MC, AF, JK), pp. 158–177.
CAV-2015-GehrDV #commutative #learning #specification: Learning Commutativity Specifications (TG, DD, MTV), pp. 307–323.
CAV-2015-IsbernerHS #automaton #framework #learning #open source: The Open-Source LearnLib — A Framework for Active Automata Learning (MI, FH, BS), pp. 487–495.
CAV-2015-Saha0M #learning #named: Alchemist: Learning Guarded Affine Functions (SS, PG, PM), pp. 440–446.
ICLP-2015-MartinezRIAT #learning #modelling #probability: Learning Probabilistic Action Models from Interpretation Transitions (DM, TR, KI, GA, CT).
ICLP-J-2015-LawRB #constraints #learning #programming #set: Learning weak constraints in answer set programming (ML, AR, KB), pp. 511–525.
SAT-2015-TuHJ #learning #named #reasoning #satisfiability: QELL: QBF Reasoning with Extended Clause Learning and Levelized SAT Solving (KHT, TCH, JHRJ), pp. 343–359.
WICSA-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.
ASE-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.
CASE-2014-HabibDBHP #android #learning: Learning human-like facial expressions for Android Phillip K. Dick (AH, SKD, ICB, DH, DOP), pp. 1159–1165.
CASE-2014-HwangLW #adaptation #learning: Adaptive reinforcement learning in box-pushing robots (KSH, JLL, WHW), pp. 1182–1187.
CASE-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.
CASE-2014-MaDLZ #learning #modelling #simulation: Modeling and simulation of product diffusion considering learning effect (KPM, XD, CFL, JZ), pp. 665–670.
CASE-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.
CASE-2014-MinakaisMW #learning: Groundhog Day: Iterative learning for building temperature control (MM, SM, JTW), pp. 948–953.
CASE-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.
CASE-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.
DAC-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.
DAC-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.
DAC-2014-FarkashHB #incremental #validation: Coverage Learned Targeted Validation for Incremental HW Changes (MF, BGH, MB), p. 6.
DATE-2014-HanKNV #learning: A deep learning methodology to proliferate golden signoff timing (SSH, ABK, SN, ASV), pp. 1–6.
DATE-2014-XuB #hybrid #question: Hybrid side-channel/machine-learning attacks on PUFs: A new threat? (XX, WB), pp. 1–6.
DRR-2014-CartonLC #interactive #learning #named: LearnPos: a new tool for interactive learning positioning (CC, AL, BC), p. ?–12.
DRR-2014-MaXA #algorithm #machine learning #segmentation #video: A machine learning based lecture video segmentation and indexing algorithm (DM, BX, GA), p. ?–8.
DRR-2014-TaoTX #documentation #learning #random #using: Document page structure learning for fixed-layout e-books using conditional random fields (XT, ZT, CX), p. ?–9.
HT-2014-AbbasiTL #learning #scalability #using: Scalable learning of users’ preferences using networked data (MAA, JT, HL), pp. 4–12.
SIGMOD-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.
SIGMOD-2014-Sedlar #compilation #how: How i learned to stop worrying and love compilers (ES), pp. 1–2.
VLDB-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.
VLDB-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.
VLDB-2014-ZouJLGWX #framework #learning #named: Mariana: Tencent Deep Learning Platform and its Applications (YZ, XJ, YL, ZG, EW, BX), pp. 1772–1777.
VLDB-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.
CSEET-2014-Ackerman #learning #re-engineering: An active learning module for an introduction to software engineering course (AFA), pp. 190–191.
CSEET-2014-BoeschS #automation #learning: Automated mentor assignment in blended learning environments (CB, KS), pp. 94–98.
CSEET-2014-Ding #learning #re-engineering #self: Self-guided learning environment for undergraduate software engineering (JD), pp. 188–189.
CSEET-2014-FranklBK #development #learning: Learning and working together as prerequisites for the development of high-quality software (GF, SB, BK), pp. 154–157.
CSEET-2014-KroppMMZ #agile #collaboration #education #learning: Teaching and learning agile collaboration (MK, AM, MM, CGZ), pp. 139–148.
CSEET-2014-PotterSDW #game studies #learning #named: InspectorX: A game for software inspection training and learning (HP, MS, LD, VW), pp. 55–64.
CSEET-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.
CSEET-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.
ITiCSE-2014-BainB #programming #question #why: Why is programming so hard to learn? (GB, IB), p. 356.
ITiCSE-2014-BerryK #game studies #learning #programming: The state of play: a notional machine for learning programming (MB, MK), pp. 21–26.
ITiCSE-2014-EckerdalKTNSM #education #learning: Teaching and learning with MOOCs: computing academics’ perspectives and engagement (AE, PK, NT, AN, JS, LM), pp. 9–14.
ITiCSE-2014-EllisH #learning #open source #re-engineering: Structuring software engineering learning within open source software participation (HJCE, GWH), p. 326.
ITiCSE-2014-EllisJBPHD #learning: Learning within a professional environment: shared ownership of an HFOSS project (HJCE, SJ, DB, LP, GWH, JD), p. 337.
ITiCSE-2014-FalknerVF #identification #learning #self: Identifying computer science self-regulated learning strategies (KF, RV, NJGF), pp. 291–296.
ITiCSE-2014-GroverCP #learning: Assessing computational learning in K-12 (SG, SC, RP), pp. 57–62.
ITiCSE-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.
ITiCSE-2014-Hijon-NeiraVPC #experience #game studies #learning #programming: Game programming for improving learning experience (RBHN, JÁVI, CPR, LC), pp. 225–230.
ITiCSE-2014-Jasute #education #geometry #interactive #learning #visualisation: An interactive visualization method of constructionist teaching and learning of geometry (EJ), p. 349.
ITiCSE-2014-KothiyalMI #learning #question #scalability: Think-pair-share in a large CS1 class: does learning really happen? (AK, SM, SI), pp. 51–56.
ITiCSE-2014-Marcos-Abed #case study #effectiveness #learning #programming: Learning computer programming: a study of the effectiveness of a COAC# (JMA), p. 333.
ITiCSE-2014-MedinaSGG #learning #student #using: Learning outcomes using objectives with computer science students (JAM, JJS, EGL, AGC), p. 339.
ITiCSE-2014-PirkerRG #education #learning #student: Motivational active learning: engaging university students in computer science education (JP, MRS, CG), pp. 297–302.
ITiCSE-2014-PriorCL #case study #experience #learning: Things coming together: learning experiences in a software studio (JP, AC, JL), pp. 129–134.
ITiCSE-2014-Rogers #learning #question: New technology, new learning? (YR), p. 1.
ITiCSE-2014-TaubBA #learning #physics: The effect of computer science on the learning of computational physics (RT, MBA, MA), p. 352.
ITiCSE-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.
ITiCSE-2014-Verwaal #learning: Team based learning in theoretical computer science (NV), p. 331.
ITiCSE-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.
ITiCSE-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.
TFPIE-2014-Walck #haskell #physics #programming: Learn Physics by Programming in Haskell (SNW), pp. 67–77.
TACAS-2014-MalerM #learning #regular expression #scalability: Learning Regular Languages over Large Alphabets (OM, IEM), pp. 485–499.
CSMR-WCRE-2014-XiaFLCW #behaviour #learning #multi #towards: Towards more accurate multi-label software behavior learning (XX, YF, DL, ZC, XW), pp. 134–143.
ICPC-2014-KaulgudAMT #comprehension #learning: Comprehension support during knowledge transitions: learning from field (VSK, KMA, JM, GT), pp. 205–206.
ICSME-2014-BinkleyL #information retrieval #learning #rank: Learning to Rank Improves IR in SE (DB, DJL), pp. 441–445.
ICSME-2014-XuanM #fault #learning #locality #metric #multi #ranking: Learning to Combine Multiple Ranking Metrics for Fault Localization (JX, MM), pp. 191–200.
STOC-2014-AwasthiBL #learning #linear #locality #power of: The power of localization for efficiently learning linear separators with noise (PA, MFB, PML), pp. 449–458.
STOC-2014-Christiano #learning #online #programming: Online local learning via semidefinite programming (PC), pp. 468–474.
STOC-2014-DanielyLS #complexity #learning: From average case complexity to improper learning complexity (AD, NL, SSS), pp. 441–448.
ICALP-v1-2014-Volkovich #bound #learning #on the: On Learning, Lower Bounds and (un)Keeping Promises (IV), pp. 1027–1038.
ICALP-v2-2014-DamsHK #learning #network: Jamming-Resistant Learning in Wireless Networks (JD, MH, TK), pp. 447–458.
LATA-2014-LaurenceLNST #learning #transducer: Learning Sequential Tree-to-Word Transducers (GL, AL, JN, SS, MT), pp. 490–502.
FM-2014-LinH #composition #concurrent #learning #model checking #synthesis: Compositional Synthesis of Concurrent Systems through Causal Model Checking and Learning (SWL, PAH), pp. 416–431.
SEFM-2014-CasselHJS #finite #learning #state machine: Learning Extended Finite State Machines (SC, FH, BJ, BS), pp. 250–264.
CHI-2014-DontchevaMBG #crowdsourcing #learning #performance: Combining crowdsourcing and learning to improve engagement and performance (MD, RRM, JRB, EMG), pp. 3379–3388.
CHI-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.
CHI-2014-GreenbergG #learning #online: Learning to fail: experiencing public failure online through crowdfunding (MDG, EG), pp. 581–590.
CHI-2014-KovacsM #learning: Smart subtitles for vocabulary learning (GK, RCM), pp. 853–862.
CHI-2014-KuleszaACFC #concept #evolution #machine learning: Structured labeling for facilitating concept evolution in machine learning (TK, SA, RC, DF, DXC), pp. 3075–3084.
CHI-2014-MentisCS #learning: Learning to see the body: supporting instructional practices in laparoscopic surgical procedures (HMM, AC, SDS), pp. 2113–2122.
CHI-2014-MonserratLZC #interactive #learning: L.IVE: an integrated interactive video-based learning environment (TJKPM, YL, SZ, XC), pp. 3399–3402.
CHI-2014-PilliasRL #design #game studies #lessons learnt #video: Designing tangible video games: lessons learned from the sifteo cubes (CP, RRB, GL), pp. 3163–3166.
CHI-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.
CSCW-2014-MillerZGG #collaboration #learning #people #research: Pair research: matching people for collaboration, learning, and productivity (RCM, HZ, EG, EG), pp. 1043–1048.
CSCW-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.
CSCW-2014-ZhuDKK #assessment #learning #performance: Reviewing versus doing: learning and performance in crowd assessment (HZ, SPD, REK, AK), pp. 1445–1455.
DHM-2014-GotoYTWS: Application of E-learning System Reality in Kyoto-style Earthen Wall Training (AG, HY, YT, ZW, HS), pp. 247–253.
DUXU-DI-2014-ChangH: Effect of Perception-Compatibility, Learning-Factor, and Symbol-Carrier on Single LED Symbol System Recognizing (CCC, TKPH), pp. 417–424.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-ELAS-2014-Portugal #design: Design, User-Experience and Teaching-Learning (CP), pp. 230–241.
DUXU-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.
HCI-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.
HCI-AIMT-2014-MikamiM #3d #effectiveness #learning: Effectiveness of Virtual Hands in 3D Learning Material (TM, SM), pp. 93–101.
HCI-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.
HCI-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.
HCI-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.
HCI-AS-2014-SchwallerKAL #feedback #gesture #learning #visual notation: Improving In-game Gesture Learning with Visual Feedback (MS, JK, LA, DL), pp. 643–653.
HCI-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.
HCI-TMT-2014-MorDHF #education #human-computer #learning #online: Teaching and Learning HCI Online (EM, MGD, EH, NF), pp. 230–241.
HCI-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.
HCI-TMT-2014-YajimaTS #collaboration #learning: Proposal of Collaborative Learning Support Method in Risk Communications (HY, NT, RS), pp. 457–465.
HIMI-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.
HIMI-AS-2014-HirashimaYH #learning #problem #word: Triplet Structure Model of Arithmetical Word Problems for Learning by Problem-Posing (TH, SY, YH), pp. 42–50.
HIMI-AS-2014-HirokawaFSY #learning #mindmap: Learning Winespeak from Mind Map of Wine Blogs (SH, BF, TS, CY), pp. 383–393.
HIMI-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.
HIMI-AS-2014-MikamiT #learning #music #performance: A Music Search System for Expressive Music Performance Learning (TM, KT), pp. 80–89.
HIMI-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.
HIMI-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.
HIMI-AS-2014-YamaguchiTT #learning #process #visualisation: Visualizing Mental Learning Processes with Invisible Mazes for Continuous Learning (TY, KT, KT), pp. 137–148.
HIMI-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.
LCT-NLE-2014-Choffat-Durr #distance #process: Distance Exchange Projects at Elementary School: A Focus on a Co-learning Process (ACD), pp. 380–387.
LCT-NLE-2014-KaprosP #learning: Empowering L&D Managers through Customisation of Inline Learning Analytics (EK, NP), pp. 282–291.
LCT-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.
LCT-NLE-2014-LimongelliS #fuzzy #modelling #personalisation #student: Fuzzy Student Modeling for Personalization of e-Learning Courses (CL, FS), pp. 292–301.
LCT-NLE-2014-Milde #editing #html #learning #online: An HTML5-Based Online Editor for Creating Annotated Learning Videos (JTM), pp. 172–179.
LCT-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.
LCT-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.
LCT-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.
LCT-NLE-2014-MoriT #development #learning: Development of a Fieldwork Support System for Group Work in Project-Based Learning (MM, AT), pp. 429–440.
LCT-NLE-2014-Piki #collaboration #learning #process #question: Learner Engagement in Computer-Supported Collaborative Learning Activities: Natural or Nurtured? (AP), pp. 107–118.
LCT-NLE-2014-Said #sorting: Card Sorting Assessing User Attitude in E-Learning (GRES), pp. 261–272.
LCT-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.
LCT-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.
LCT-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.
LCT-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.
LCT-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.
LCT-TRE-2014-Bharali #learning #online #process: Enhancing Online Learning Activities for Groups in Flipped Classrooms (RB), pp. 269–276.
LCT-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.
LCT-TRE-2014-Castro #case study #collaboration #learning #named: Mosca — A Case Study on Collaborative Work — Combining Dimensions while Learning (SC), pp. 388–396.
LCT-TRE-2014-EradzeL #design #interactive #learning: Interrelation between Pedagogical Design and Learning Interaction Patterns in different Virtual Learning Environments (ME, ML), pp. 23–32.
LCT-TRE-2014-Hayes14a #approach #development #game studies #learning #simulation: An Approach to Holistic Development of Serious Games and Learning Simulations (ATH), pp. 42–49.
LCT-TRE-2014-HiramatsuIFS #development #learning #using: Development of the Learning System for Outdoor Study Using Zeigarnik Effect (YH, AI, MF, FS), pp. 127–137.
LCT-TRE-2014-IkedaS #learning: Dream Drill: A Bedtime Learning Application (AI, IS), pp. 138–145.
LCT-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.
LCT-TRE-2014-MartinezMLLC #3d #interactive #learning: Supporting Learning with 3D Interactive Applications in Early Years (ACM, MJMS, MLS, DCPL, MC), pp. 11–22.
LCT-TRE-2014-MartinWH #interactive #learning #mobile: Sensor Based Interaction Mechanisms in Mobile Learning (KUM, MW, WH), pp. 165–172.
LCT-TRE-2014-OliveiraM #learning #network #research: Digital Identity of Researchers and Their Personal Learning Network (NRO, LM), pp. 467–477.
LCT-TRE-2014-ShahoumianSZPH #education #learning #simulation: Blended Simulation Based Medical Education: A Complex Learning/Training Opportunity (AS, MS, MZ, GP, JH), pp. 478–485.
LCT-TRE-2014-ShimizuO #effectiveness #learning #question: Which Is More Effective for Learning German and Japanese Language, Paper or Digital? (RS, KO), pp. 309–318.
LCT-TRE-2014-SzklannyW #learning #prototype: Prototyping M-Learning Course on the Basis of Puzzle Learning Methodology (KS, MW), pp. 215–226.
LCT-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.
AdaEurope-2014-Laine #lessons learnt: Lessons Learned and Easily Forgotten (RL), pp. 1–6.
HILT-2014-BarnesT #ada #design #lessons learnt: Ada 83 to Ada 2012: lessons learned over 30 years of language design (JB, STT), pp. 3–4.
ICEIS-v1-2014-ShakirIB #machine learning #topic: Machine Learning Techniques for Topic Spotting (NS, EI, ISB), pp. 450–455.
ICEIS-v2-2014-MahmoudBAG #approach #learning: A New Approach Based on Learning Services to Generate Appropriate Learning Paths (CBM, FB, MHA, FG), pp. 643–646.
ICEIS-v2-2014-OtonBGGB #learning #metadata #using: Description of Accessible Learning Resources by Using Metadata (SO, CB, EG, AGC, RB), pp. 620–626.
ICEIS-v2-2014-ZhengJL #hybrid #learning #taxonomy #using: Cross-Sensor Iris Matching using Patch-based Hybrid Dictionary Learning (BRZ, DYJ, YHL), pp. 169–174.
ICEIS-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.
ICEIS-v3-2014-BalinaAMS #development #metamodelling: Meta Model of e-Learning Materials Development (SB, IA, IM, ES), pp. 150–155.
ICEIS-v3-2014-PaulinsBA #visualisation: e-Learning Material Presentation and Visualization Types and Schemes (NP, SB, IA), pp. 138–143.
CIKM-2014-DeBBGC #learning #linear: Learning a Linear Influence Model from Transient Opinion Dynamics (AD, SB, PB, NG, SC), pp. 401–410.
CIKM-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.
CIKM-2014-GoncalvesDCSZB #learning #multi: Multi-task Sparse Structure Learning (ARG, PD, SC, VS, FJVZ, AB), pp. 451–460.
CIKM-2014-JinZXDLH #learning #multi: Multi-task Multi-view Learning for Heterogeneous Tasks (XJ, FZ, HX, CD, PL, QH), pp. 441–450.
CIKM-2014-MaoWHO #classification #learning #linear #multi: Nonlinear Classification via Linear SVMs and Multi-Task Learning (XM, OW, WH, PO), pp. 1955–1958.
CIKM-2014-PfeifferNB #learning #network #probability #using: Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference (JJPI, JN, PNB), pp. 639–648.
CIKM-2014-PimplikarGBP #learning: Learning to Propagate Rare Labels (RP, DG, DB, GRP), pp. 201–210.
CIKM-2014-ShiKBLH #learning #named #recommendation: CARS2: Learning Context-aware Representations for Context-aware Recommendations (YS, AK, LB, ML, AH), pp. 291–300.
CIKM-2014-VinzamuriLR #learning: Active Learning based Survival Regression for Censored Data (BV, YL, CKR), pp. 241–250.
CIKM-2014-WangMC #learning #parametricity: Structure Learning via Parameter Learning (WYW, KM, WWC), pp. 1199–1208.
CIKM-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.
CIKM-2014-XiePLW #framework #image #learning #multi: A Cross-modal Multi-task Learning Framework for Image Annotation (LX, PP, YL, SW), pp. 431–440.
CIKM-2014-YangTZ #learning #streaming: Active Learning for Streaming Networked Data (ZY, JT, YZ), pp. 1129–1138.
CIKM-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.
CIKM-2014-YuX #interactive #learning #network #predict #scalability #social: Learning Interactions for Social Prediction in Large-scale Networks (XY, JX), pp. 161–170.
CIKM-2014-ZhongPXYM #adaptation #collaboration #learning #recommendation: Adaptive Pairwise Preference Learning for Collaborative Recommendation with Implicit Feedbacks (HZ, WP, CX, ZY, ZM), pp. 1999–2002.
CIKM-2014-ZhuSY #information retrieval #learning #taxonomy: Cross-Modality Submodular Dictionary Learning for Information Retrieval (FZ, LS, MY), pp. 1479–1488.
ECIR-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.
ECIR-2014-BreussT #interactive #learning #recommendation #social #social media: Learning from User Interactions for Recommending Content in Social Media (MB, MT), pp. 598–604.
ECIR-2014-FiliceCCB #effectiveness #kernel #learning #online: Effective Kernelized Online Learning in Language Processing Tasks (SF, GC, DC, RB), pp. 347–358.
ECIR-2014-NainiA #feature model #learning #rank: Exploiting Result Diversification Methods for Feature Selection in Learning to Rank (KDN, ISA), pp. 455–461.
ECIR-2014-QiDCW #information management #learning: Deep Learning for Character-Based Information Extraction (YQ, SGD, RC, JW), pp. 668–674.
ICML-c1-2014-AroraBGM #bound #learning: Provable Bounds for Learning Some Deep Representations (SA, AB, RG, TM), pp. 584–592.
ICML-c1-2014-DenisGH #bound #learning #matrix: Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning (FD, MG, AH), pp. 449–457.
ICML-c1-2014-DickGS #learning #markov #online #process #sequence: Online Learning in Markov Decision Processes with Changing Cost Sequences (TD, AG, CS), pp. 512–520.
ICML-c1-2014-JainT #bound #independence #learning: (Near) Dimension Independent Risk Bounds for Differentially Private Learning (PJ, AGT), pp. 476–484.
ICML-c1-2014-LacosteMLL #learning: Agnostic Bayesian Learning of Ensembles (AL, MM, FL, HL), pp. 611–619.
ICML-c1-2014-LajugieBA #clustering #learning #metric #problem: Large-Margin Metric Learning for Constrained Partitioning Problems (RL, FRB, SA), pp. 297–305.
ICML-c1-2014-LuoS #learning #online #towards: Towards Minimax Online Learning with Unknown Time Horizon (HL, RES), pp. 226–234.
ICML-c1-2014-MohriM #algorithm #learning #optimisation: Learning Theory and Algorithms for revenue optimization in second price auctions with reserve (MM, AMM), pp. 262–270.
ICML-c1-2014-RooshenasL #interactive #learning #network: Learning Sum-Product Networks with Direct and Indirect Variable Interactions (AR, DL), pp. 710–718.
ICML-c1-2014-ShalitC #coordination #learning #matrix #orthogonal: Coordinate-descent for learning orthogonal matrices through Givens rotations (US, GC), pp. 548–556.
ICML-c1-2014-ShiZ #learning #online: Online Bayesian Passive-Aggressive Learning (TS, JZ), pp. 378–386.
ICML-c1-2014-SolomonRGB #learning: Wasserstein Propagation for Semi-Supervised Learning (JS, RMR, LJG, AB), pp. 306–314.
ICML-c1-2014-TandonR #graph #learning: Learning Graphs with a Few Hubs (RT, PDR), pp. 602–610.
ICML-c1-2014-Yu0KD #learning #multi #scalability: Large-scale Multi-label Learning with Missing Labels (HFY, PJ, PK, ISD), pp. 593–601.
ICML-c2-2014-AffandiFAT #kernel #learning #parametricity #process: Learning the Parameters of Determinantal Point Process Kernels (RHA, EBF, RPA, BT), pp. 1224–1232.
ICML-c2-2014-AminHK #learning: Learning from Contagion (Without Timestamps) (KA, HH, MK), pp. 1845–1853.
ICML-c2-2014-AndoniPV0 #learning #network: Learning Polynomials with Neural Networks (AA, RP, GV, LZ), pp. 1908–1916.
ICML-c2-2014-AziziAG #composition #learning #network: Learning Modular Structures from Network Data and Node Variables (EA, EA, JEG), pp. 1440–1448.
ICML-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.
ICML-c2-2014-Bou-AmmarERT #learning #multi #online #policy: Online Multi-Task Learning for Policy Gradient Methods (HBA, EE, PR, MET), pp. 1206–1214.
ICML-c2-2014-BrunskillL #learning: PAC-inspired Option Discovery in Lifelong Reinforcement Learning (EB, LL), pp. 316–324.
ICML-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.
ICML-c2-2014-CohenW #commutative #learning: Learning the Irreducible Representations of Commutative Lie Groups (TC, MW), pp. 1755–1763.
ICML-c2-2014-DuLBS #information management #learning #network: Influence Function Learning in Information Diffusion Networks (ND, YL, MFB, LS), pp. 2016–2024.
ICML-c2-2014-FangCL #graph #learning: Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically (YF, KCCC, HWL), pp. 406–414.
ICML-c2-2014-GrandeWH #learning #performance #process: Sample Efficient Reinforcement Learning with Gaussian Processes (RCG, TJW, JPH), pp. 1332–1340.
ICML-c2-2014-HoangLJK #learning #process: Nonmyopic ϵ-Bayes-Optimal Active Learning of Gaussian Processes (TNH, BKHL, PJ, MSK), pp. 739–747.
ICML-c2-2014-HoulsbyHG #learning #matrix #robust: Cold-start Active Learning with Robust Ordinal Matrix Factorization (NH, JMHL, ZG), pp. 766–774.
ICML-c2-2014-HuS #machine learning #multi #predict: Multi-period Trading Prediction Markets with Connections to Machine Learning (JH, AJS), pp. 1773–1781.
ICML-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.
ICML-c2-2014-KricheneDB #convergence #learning #on the: On the convergence of no-regret learning in selfish routing (WK, BD, AMB), pp. 163–171.
ICML-c2-2014-LevineK #learning #network #optimisation #policy: Learning Complex Neural Network Policies with Trajectory Optimization (SL, VK), pp. 829–837.
ICML-c2-2014-LiG #classification #learning #representation #semantics: Latent Semantic Representation Learning for Scene Classification (XL, YG), pp. 532–540.
ICML-c2-2014-LimL #learning #metric #performance #ranking: Efficient Learning of Mahalanobis Metrics for Ranking (DL, GRGL), pp. 1980–1988.
ICML-c2-2014-LinK #constraints #learning #performance #representation: Stable and Efficient Representation Learning with Nonnegativity Constraints (THL, HTK), pp. 1323–1331.
ICML-c2-2014-LinYHY #distance #learning: Geodesic Distance Function Learning via Heat Flow on Vector Fields (BL, JY, XH, JY), pp. 145–153.
ICML-c2-2014-LiuD #learning #problem #set: Learnability of the Superset Label Learning Problem (LPL, TGD), pp. 1629–1637.
ICML-c2-2014-LiZ #higher-order #learning #problem: High Order Regularization for Semi-Supervised Learning of Structured Output Problems (YL, RSZ), pp. 1368–1376.
ICML-c2-2014-LiZ0 #learning #multi: Bayesian Max-margin Multi-Task Learning with Data Augmentation (CL, JZ, JC), pp. 415–423.
ICML-c2-2014-MengEH #learning #modelling #visual notation: Learning Latent Variable Gaussian Graphical Models (ZM, BE, AOHI), pp. 1269–1277.
ICML-c2-2014-MizrahiDF #learning #linear #markov #parallel #random: Linear and Parallel Learning of Markov Random Fields (YDM, MD, NdF), pp. 199–207.
ICML-c2-2014-MnihG #learning #network: Neural Variational Inference and Learning in Belief Networks (AM, KG), pp. 1791–1799.
ICML-c2-2014-NiuDPS #approximate #learning #multi: Transductive Learning with Multi-class Volume Approximation (GN, BD, MCdP, MS), pp. 1377–1385.
ICML-c2-2014-PandeyD #learning #network: Learning by Stretching Deep Networks (GP, AD), pp. 1719–1727.
ICML-c2-2014-PentinaL #bound #learning: A PAC-Bayesian bound for Lifelong Learning (AP, CHL), pp. 991–999.
ICML-c2-2014-QinLJ #learning #optimisation: Sparse Reinforcement Learning via Convex Optimization (ZQ, WL, FJ), pp. 424–432.
ICML-c2-2014-ReedSZL #interactive #learning: Learning to Disentangle Factors of Variation with Manifold Interaction (SR, KS, YZ, HL), pp. 1431–1439.
ICML-c2-2014-RippelGA #learning #order: Learning Ordered Representations with Nested Dropout (OR, MAG, RPA), pp. 1746–1754.
ICML-c2-2014-RodriguesPR #classification #learning #multi #process: Gaussian Process Classification and Active Learning with Multiple Annotators (FR, FCP, BR), pp. 433–441.
ICML-c2-2014-SantosZ #learning: Learning Character-level Representations for Part-of-Speech Tagging (CNdS, BZ), pp. 1818–1826.
ICML-c2-2014-SilvaKB #learning: Active Learning of Parameterized Skills (BCdS, GK, AGB), pp. 1737–1745.
ICML-c2-2014-SongGJMHD #learning #locality #on the: On learning to localize objects with minimal supervision (HOS, RBG, SJ, JM, ZH, TD), pp. 1611–1619.
ICML-c2-2014-SunIM #classification #learning #linear: Learning Mixtures of Linear Classifiers (YS, SI, AM), pp. 721–729.
ICML-c2-2014-SunM #geometry #learning #statistics: An Information Geometry of Statistical Manifold Learning (KS, SMM), pp. 1–9.
ICML-c2-2014-TrigeorgisBZS #learning: A Deep Semi-NMF Model for Learning Hidden Representations (GT, KB, SZ, BWS), pp. 1692–1700.
ICML-c2-2014-WangHS #learning: Active Transfer Learning under Model Shift (XW, TKH, JS), pp. 1305–1313.
ICML-c2-2014-WangNH #distance #learning #metric #robust: Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization (HW, FN, HH), pp. 1836–1844.
ICML-c2-2014-WangSSMK #learning #metric: Two-Stage Metric Learning (JW, KS, FS, SMM, AK), pp. 370–378.
ICML-c2-2014-WenYG #learning #nondeterminism #robust: Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification (JW, CNY, RG), pp. 631–639.
ICML-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.
ICPR-2014-AkinM #detection #learning #online: Online Learning and Detection with Part-Based, Circulant Structure (OA, KM), pp. 4229–4233.
ICPR-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.
ICPR-2014-Alvarez-MezaMC #adaptation #learning #video: Correntropy-Based Adaptive Learning to Support Video Surveillance Systems (AMÁM, SMG, GCD), pp. 2590–2595.
ICPR-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.
ICPR-2014-ArvanitopoulosBT #analysis #learning: Laplacian Support Vector Analysis for Subspace Discriminative Learning (NA, DB, AT), pp. 1609–1614.
ICPR-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.
ICPR-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.
ICPR-2014-BertonL #graph #learning: Graph Construction Based on Labeled Instances for Semi-supervised Learning (LB, AdAL), pp. 2477–2482.
ICPR-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.
ICPR-2014-CaiTF #learning #recognition #taxonomy: Learning Pose Dictionary for Human Action Recognition (JxC, XT, GCF), pp. 381–386.
ICPR-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.
ICPR-2014-ChengZHT #learning #recognition: Semi-supervised Learning for RGB-D Object Recognition (YC, XZ, KH, TT), pp. 2377–2382.
ICPR-2014-ChenK14a #learning: Learning to Count with Back-propagated Information (KC, JKK), pp. 4672–4677.
ICPR-2014-ChenZW #identification #learning #metric: Relevance Metric Learning for Person Re-identification by Exploiting Global Similarities (JC, ZZ, YW), pp. 1657–1662.
ICPR-2014-CheplyginaSTPLB #classification #learning #multi: Classification of COPD with Multiple Instance Learning (VC, LS, DMJT, JJHP, ML, MdB), pp. 1508–1513.
ICPR-2014-CruzSC #on the: On Meta-learning for Dynamic Ensemble Selection (RMOC, RS, GDCC), pp. 1230–1235.
ICPR-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.
ICPR-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.
ICPR-2014-FangZ #classification #learning: Cross Domain Shared Subspace Learning for Unsupervised Transfer Classification (ZF, ZZ), pp. 3927–3932.
ICPR-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.
ICPR-2014-FiratCV #detection #learning #representation: Representation Learning for Contextual Object and Region Detection in Remote Sensing (OF, GC, FTYV), pp. 3708–3713.
ICPR-2014-FornoniC #learning #naive bayes #recognition: Scene Recognition with Naive Bayes Non-linear Learning (MF, BC), pp. 3404–3409.
ICPR-2014-GanSZ #learning: An Extended Isomap for Manifold Topology Learning with SOINN Landmarks (QG, FS, JZ), pp. 1579–1584.
ICPR-2014-GeDGC #learning: Background Subtraction with Dynamic Noise Sampling and Complementary Learning (WG, YD, ZG, YC), pp. 2341–2346.
ICPR-2014-GengWX #adaptation #estimation #learning: Facial Age Estimation by Adaptive Label Distribution Learning (XG, QW, YX), pp. 4465–4470.
ICPR-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.
ICPR-2014-GuoZLCZ #clustering #kernel #learning #multi: Multiple Kernel Learning Based Multi-view Spectral Clustering (DG, JZ, XL, YC, CZ), pp. 3774–3779.
ICPR-2014-HooKPC #comprehension #image #learning #random: Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding (WLH, TKK, YP, CSC), pp. 3434–3439.
ICPR-2014-HouYW #adaptation #learning #recognition #self: Domain Adaptive Self-Taught Learning for Heterogeneous Face Recognition (CAH, MCY, YCFW), pp. 3068–3073.
ICPR-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.
ICPR-2014-JhuoL #detection #learning #multi #video: Video Event Detection via Multi-modality Deep Learning (IHJ, DTL), pp. 666–671.
ICPR-2014-KhoshrouCT #learning #multi #video: Active Learning from Video Streams in a Multi-camera Scenario (SK, JSC, LFT), pp. 1248–1253.
ICPR-2014-KrauseGDLF #fine-grained #learning #recognition: Learning Features and Parts for Fine-Grained Recognition (JK, TG, JD, LJL, FFL), pp. 26–33.
ICPR-2014-KumarG #documentation #keyword #learning: Bayesian Active Learning for Keyword Spotting in Handwritten Documents (GK, VG), pp. 2041–2046.
ICPR-2014-LeiSLCXP #learning #metric #similarity: Humanoid Robot Imitation with Pose Similarity Metric Learning (JL, MS, ZNL, CC, XX, SP), pp. 4240–4245.
ICPR-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.
ICPR-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.
ICPR-2014-LiuYHTH #learning #recognition #visual notation: Semi-supervised Learning for Cross-Device Visual Location Recognition (PL, PY, KH, TT, HWH), pp. 2873–2878.
ICPR-2014-LiuZC #identification #learning #metric #multi #parametricity: Parametric Local Multi-modal Metric Learning for Person Re-identification (KL, ZCZ, AC), pp. 2578–2583.
ICPR-2014-LuoJ #encoding #image #learning #retrieval #semantics: Learning Semantic Binary Codes by Encoding Attributes for Image Retrieval (JL, ZJ), pp. 279–284.
ICPR-2014-ManfrediGC #energy #graph #image #learning #segmentation: Learning Graph Cut Energy Functions for Image Segmentation (MM, CG, RC), pp. 960–965.
ICPR-2014-MarcaciniDHR #approach #clustering #documentation #learning #metric: Privileged Information for Hierarchical Document Clustering: A Metric Learning Approach (RMM, MAD, ERH, SOR), pp. 3636–3641.
ICPR-2014-MontagnerjH #machine learning: A Machine Learning Based Method for Staff Removal (IdSM, RHJ, NSTH), pp. 3162–3167.
ICPR-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.
ICPR-2014-NieJ #learning #linear #using: Feature Learning Using Bayesian Linear Regression Model (SN, QJ), pp. 1502–1507.
ICPR-2014-NieKZ #learning #recognition #using: Periocular Recognition Using Unsupervised Convolutional RBM Feature Learning (LN, AK, SZ), pp. 399–404.
ICPR-2014-NilufarP #detection #learning #programming: Learning to Detect Contours with Dynamic Programming Snakes (SN, TJP), pp. 984–989.
ICPR-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.
ICPR-2014-PatriciaTC #adaptation #learning #multi #performance: Multi-source Adaptive Learning for Fast Control of Prosthetics Hand (NP, TT, BC), pp. 2769–2774.
ICPR-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.
ICPR-2014-PhamKC #graph #image #learning: Semi-supervised Learning on Bi-relational Graph for Image Annotation (HDP, KHK, SC), pp. 2465–2470.
ICPR-2014-PillaiFR #classification #learning #multi: Learning of Multilabel Classifiers (IP, GF, FR), pp. 3452–3456.
ICPR-2014-RenYZH #classification #image #learning #nearest neighbour: Learning Convolutional Nonlinear Features for K Nearest Neighbor Image Classification (WR, YY, JZ, KH), pp. 4358–4363.
ICPR-2014-RiabchenkoKC #generative #learning #modelling: Learning Generative Models of Object Parts from a Few Positive Examples (ER, JKK, KC), pp. 2287–2292.
ICPR-2014-RozzaMP #graph #kernel #learning #novel: A Novel Graph-Based Fisher Kernel Method for Semi-supervised Learning (AR, MM, AP), pp. 3786–3791.
ICPR-2014-SaitoAFRSGC #learning #using: Active Semi-supervised Learning Using Optimum-Path Forest (PTMS, WPA, AXF, PJdR, CTNS, JFG, MHdC), pp. 3798–3803.
ICPR-2014-SatoKSK #classification #learning #multi: Learning Multiple Complex Features Based on Classification Results (YS, KK, YS, MK), pp. 3369–3373.
ICPR-2014-SavakisRP #difference #gesture #learning #using: Gesture Control Using Active Difference Signatures and Sparse Learning (AES, RR, RWP), pp. 3969–3974.
ICPR-2014-ShenHSGM #framework #interactive #learning: Interactive Framework for Insect Tracking with Active Learning (MS, WH, PS, CGG, DM), pp. 2733–2738.
ICPR-2014-StraehleKKH #learning #multi #random: Multiple Instance Learning with Response-Optimized Random Forests (CNS, MK, UK, FAH), pp. 3768–3773.
ICPR-2014-UmakanthanDFS #learning #multi #process #representation #taxonomy: Multiple Instance Dictionary Learning for Activity Representation (SU, SD, CF, SS), pp. 1377–1382.
ICPR-2014-VellankiDVP #learning #parametricity: Nonparametric Discovery of Learning Patterns and Autism Subgroups from Therapeutic Data (PV, TVD, SV, DQP), pp. 1828–1833.
ICPR-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.
ICPR-2014-WangGJ #learning #using: Learning with Hidden Information Using a Max-Margin Latent Variable Model (ZW, TG, QJ), pp. 1389–1394.
ICPR-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.
ICPR-2014-WangWJ #learning: Learning with Hidden Information (ZW, XW, QJ), pp. 238–243.
ICPR-2014-WangZWB #learning #modelling: Learning Room Occupancy Patterns from Sparsely Recovered Light Transport Models (QW, XZ, MW, KLB), pp. 1987–1992.
ICPR-2014-WanHA #image #learning #recognition: Indoor Scene Recognition from RGB-D Images by Learning Scene Bases (SW, CH, JKA), pp. 3416–3421.
ICPR-2014-WatanabeW #analysis #component #distance #learning #metric #performance: Logistic Component Analysis for Fast Distance Metric Learning (KW, TW), pp. 1278–1282.
ICPR-2014-WuHYWT #image #network #segmentation: Early Hierarchical Contexts Learned by Convolutional Networks for Image Segmentation (ZW, YH, YY, LW, TT), pp. 1538–1543.
ICPR-2014-WuJ #detection #learning: Learning the Deep Features for Eye Detection in Uncontrolled Conditions (YW, QJ), pp. 455–459.
ICPR-2014-WuLWHJ #learning #multi: Multi-label Learning with Missing Labels (BW, ZL, SW, BGH, QJ), pp. 1964–1968.
ICPR-2014-WuS #learning #multi #recognition: Regularized Multi-view Multi-metric Learning for Action Recognition (XW, SKS), pp. 471–476.
ICPR-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.
ICPR-2014-XieUKG #incremental #learning: Incremental Learning with Support Vector Data Description (WX, SU, SK, MG), pp. 3904–3909.
ICPR-2014-XuS #learning #network #using: Bayesian Network Structure Learning Using Causality (ZX, SNS), pp. 3546–3551.
ICPR-2014-YangN #integration #learning #multi: Semi-supervised Learning of Geospatial Objects through Multi-modal Data Integration (YY, SN), pp. 4062–4067.
ICPR-2014-YangXWL #learning #realtime: Real-Time Tracking via Deformable Structure Regression Learning (XY, QX, SW, PL), pp. 2179–2184.
ICPR-2014-YangYH #learning: Diversity-Based Ensemble with Sample Weight Learning (CY, XCY, HWH), pp. 1236–1241.
ICPR-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.
ICPR-2014-YiLLL #identification #learning #metric: Deep Metric Learning for Person Re-identification (DY, ZL, SL, SZL), pp. 34–39.
ICPR-2014-YinYPH #case study #classification #learning: Shallow Classification or Deep Learning: An Experimental Study (XCY, CY, WYP, HWH), pp. 1904–1909.
ICPR-2014-YooJKC #learning #optimisation: Transfer Learning of Motion Patterns in Traffic Scene via Convex Optimization (YJY, HJ, SWK, JYC), pp. 4158–4163.
ICPR-2014-ZenRS #distance #learning #matrix #metric: Simultaneous Ground Metric Learning and Matrix Factorization with Earth Mover’s Distance (GZ, ER, NS), pp. 3690–3695.
ICPR-2014-ZhangM14a #detection #learning #multi: Simultaneous Detection of Multiple Facial Action Units via Hierarchical Task Structure Learning (XZ, MHM), pp. 1863–1868.
ICPR-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.
ICPR-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.
ICPR-2014-ZhuS #learning #recognition #taxonomy: Correspondence-Free Dictionary Learning for Cross-View Action Recognition (FZ, LS), pp. 4525–4530.
ICPR-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.
KDD-2014-Bengio #learning #scalability: Scaling up deep learning (YB), p. 1966.
KDD-2014-BensonRS #learning #multi #network #scalability: Learning multifractal structure in large networks (ARB, CR, SS), pp. 1326–1335.
KDD-2014-DalessandroCRPWP #learning #online #scalability: Scalable hands-free transfer learning for online advertising (BD, DC, TR, CP, MHW, FJP), pp. 1573–1582.
KDD-2014-GaddeAO #graph #learning #using: Active semi-supervised learning using sampling theory for graph signals (AG, AA, AO), pp. 492–501.
KDD-2014-GohR #learning: Box drawings for learning with imbalanced data (STG, CR), pp. 333–342.
KDD-2014-GongZFY #learning #multi #performance: Efficient multi-task feature learning with calibration (PG, JZ, WF, JY), pp. 761–770.
KDD-2014-GrabockaSWS #learning: Learning time-series shapelets (JG, NS, MW, LST), pp. 392–401.
KDD-2014-Kushnir #adaptation #kernel #learning: Active-transductive learning with label-adapted kernels (DK), pp. 462–471.
KDD-2014-LanSB #analysis #learning: Time-varying learning and content analytics via sparse factor analysis (ASL, CS, RGB), pp. 452–461.
KDD-2014-LiangRR #learning #personalisation: Personalized search result diversification via structured learning (SL, ZR, MdR), pp. 751–760.
KDD-2014-Mullainathan #machine learning #question #social: Bugbears or legitimate threats?: (social) scientists’ criticisms of machine learning? (SM), p. 4.
KDD-2014-PerozziAS #learning #named #online #social: DeepWalk: online learning of social representations (BP, RAR, SS), pp. 701–710.
KDD-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.
KDD-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.
KDD-2014-QianHJPZ #approach #distance #learning #metric #using: Distance metric learning using dropout: a structured regularization approach (QQ, JH, RJ, JP, SZ), pp. 323–332.
KDD-2014-Rudin #algorithm #machine learning: Algorithms for interpretable machine learning (CR), p. 1519.
KDD-2014-Salakhutdinov #learning: Deep learning (RS), p. 1973.
KDD-2014-ShaoAK #concept #data type #learning #prototype: Prototype-based learning on concept-drifting data streams (JS, ZA, SK), pp. 412–421.
KDD-2014-SrikantA #machine learning #programming #using: A system to grade computer programming skills using machine learning (SS, VA), pp. 1887–1896.
KDD-2014-TayebiEGB #embedded #learning #predict #using: Spatially embedded co-offence prediction using supervised learning (MAT, ME, UG, PLB), pp. 1789–1798.
KDD-2014-VasishtDVK #classification #learning #multi: Active learning for sparse bayesian multilabel classification (DV, ACD, MV, AK), pp. 472–481.
KDD-2014-WangNH #adaptation #induction #learning #scalability: Large-scale adaptive semi-supervised learning via unified inductive and transductive model (DW, FN, HH), pp. 482–491.
KDD-2014-WangSE #collaboration #learning #permutation: Active collaborative permutation learning (JW, NS, JE), pp. 502–511.
KDD-2014-WangSW #learning #modelling: Unsupervised learning of disease progression models (XW, DS, FW), pp. 85–94.
KDD-2014-XuL #behaviour #learning #problem: Product selection problem: improve market share by learning consumer behavior (SX, JCSL), pp. 851–860.
KDD-2014-YangH #learning #parametricity: Learning with dual heterogeneity: a nonparametric bayes model (HY, JH), pp. 582–590.
KDD-2014-ZhangTMF #learning #network: Supervised deep learning with auxiliary networks (JZ, GT, YM, WF), pp. 353–361.
KDD-2014-ZhouC #adaptation #documentation #learning #rank: Unifying learning to rank and domain adaptation: enabling cross-task document scoring (MZ, KCCC), pp. 781–790.
KDIR-2014-Bleiweiss #execution #machine learning #using: SoC Processor Discovery for Program Execution Matching Using Unsupervised Machine Learning (AB), pp. 192–201.
KDIR-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.
KDIR-2014-SuciuICDP #learning #word: Learning Good Opinions from Just Two Words Is Not Bad (DAS, VVI, ACC, MD, RP), pp. 233–241.
KEOD-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.
KMIS-2014-AtrashAM #collaboration #learning: Supporting Organizational Learning with Collaborative Annotation (AA, MHA, CM), pp. 237–244.
KMIS-2014-BartuskovaK #information management #learning: Knowledge Management and Sharing in E-Learning — Hierarchical System for Managing Learning Resources (AB, OK), pp. 179–185.
KMIS-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.
KMIS-2014-HisakaneS #learning #visualisation: A Visualization System of Discussion Structure in Case Method Learning (DH, MS), pp. 126–132.
KMIS-2014-SmirnovS #implementation #information management #lessons learnt: Role-Driven Knowledge Management Implementation — Lessons Learned (AVS, NS), pp. 36–43.
KR-2014-KonevLOW #learning #lightweight #logic #ontology: Exact Learning of Lightweight Description Logic Ontologies (BK, CL, AO, FW).
KR-2014-Michael #learning #predict: Simultaneous Learning and Prediction (LM).
MLDM-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.
MLDM-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.
MLDM-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.
MLDM-2014-KuleshovB #data mining #learning #mining: Manifold Learning in Data Mining Tasks (APK, AVB), pp. 119–133.
MLDM-2014-NeumannHRL #case study #experience #learning: A Robot Waiter Learning from Experiences (BN, LH, PR, JL), pp. 285–299.
MLDM-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.
RecSys-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.
RecSys-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.
RecSys-2014-SaveskiM #learning #recommendation: Item cold-start recommendations: learning local collective embeddings (MS, AM), pp. 89–96.
SEKE-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.
SEKE-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.
SEKE-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.
SEKE-2014-SinghS #machine learning #requirements #using: Software Requirement Prioritization using Machine Learning (DS, AS), pp. 701–704.
SIGIR-2014-CanCM #feedback #modelling #ranking: Incorporating query-specific feedback into learning-to-rank models (EFC, WBC, RM), pp. 1035–1038.
SIGIR-2014-CormackG #bibliography #evaluation #protocol: Evaluation of machine-learning protocols for technology-assisted review in electronic discovery (GVC, MRG), pp. 153–162.
SIGIR-2014-CostaCS #learning #modelling #ranking: Learning temporal-dependent ranking models (MC, FMC, MJS), pp. 757–766.
SIGIR-2014-EfronWS #learning #query: Learning sufficient queries for entity filtering (ME, CW, GS), pp. 1091–1094.
SIGIR-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.
SIGIR-2014-JiangKCC #behaviour #learning #query: Learning user reformulation behavior for query auto-completion (JYJ, YYK, PYC, PJC), pp. 445–454.
SIGIR-2014-LengCL #image #learning #random #retrieval #scalability: Random subspace for binary codes learning in large scale image retrieval (CL, JC, HL), pp. 1031–1034.
SIGIR-2014-LiuL #learning #probability #segmentation #word: Probabilistic ensemble learning for vietnamese word segmentation (WL, LL), pp. 931–934.
SIGIR-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.
SIGIR-2014-PanYMLNR #image #learning: Click-through-based cross-view learning for image search (YP, TY, TM, HL, CWN, YR), pp. 717–726.
SIGIR-2014-QiuCYLL #learning #personalisation #ranking: Item group based pairwise preference learning for personalized ranking (SQ, JC, TY, CL, HL), pp. 1219–1222.
SIGIR-2014-SokolovHR #learning #query: Learning to translate queries for CLIR (AS, FH, SR), pp. 1179–1182.
SIGIR-2014-SpinaGA #detection #learning #monitoring #online #similarity #topic: Learning similarity functions for topic detection in online reputation monitoring (DS, JG, EA), pp. 527–536.
SIGIR-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.
SIGIR-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.
SIGIR-2014-WuMHR #image #learning #personalisation: Learning to personalize trending image search suggestion (CCW, TM, WHH, YR), pp. 727–736.
SIGIR-2014-YuWZTSZ #learning #rank: Hashing with List-Wise learning to rank (ZY, FW, YZ, ST, JS, YZ), pp. 999–1002.
SIGIR-2014-ZhuLGCN #learning: Learning for search result diversification (YZ, YL, JG, XC, SN), pp. 293–302.
SIGIR-2014-ZhuNG #adaptation #learning #random #social: An adaptive teleportation random walk model for learning social tag relevance (XZ, WN, MG), pp. 223–232.
MoDELS-2014-BakiSCMF #learning #model transformation: Learning Implicit and Explicit Control in Model Transformations by Example (IB, HAS, QC, PM, MF), pp. 636–652.
MoDELS-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.
MoDELS-2014-BakiSCMF #learning #model transformation: Learning Implicit and Explicit Control in Model Transformations by Example (IB, HAS, QC, PM, MF), pp. 636–652.
MoDELS-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.
RE-2014-MaalejG #lessons learnt: Capturing and sharing domain knowledge with business rules lessons learned from a global software vendor (WM, SG), pp. 364–373.
SAC-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.
SAC-2014-DhanjalC #learning #network: Learning reputation in an authorship network (CD, SC), pp. 1724–1726.
SAC-2014-LiWL #learning #mobile #online #recognition: Online learning with mobile sensor data for user recognition (HGL, XW, ZL), pp. 64–70.
SAC-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.
SAC-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.
FSE-2014-AllamanisBBS #learning: Learning natural coding conventions (MA, ETB, CB, CAS), pp. 281–293.
FSE-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.
FSE-2014-YeBL #debugging #learning #rank #using: Learning to rank relevant files for bug reports using domain knowledge (XY, RCB, CL), pp. 689–699.
ICSE-2014-HeWYZ #learning #reasoning: Symbolic assume-guarantee reasoning through BDD learning (FH, BYW, LY, LZ), pp. 1071–1082.
ICSE-2014-JingYZWL #fault #learning #predict #taxonomy: Dictionary learning based software defect prediction (XYJ, SY, ZWZ, SSW, JL), pp. 414–423.
ICSE-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.
ICSE-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.
ASPLOS-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.
HPCA-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.
OSDI-2014-ChilimbiSAK #learning #performance #scalability: Project Adam: Building an Efficient and Scalable Deep Learning Training System (TMC, YS, JA, KK), pp. 571–582.
OSDI-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.
CAV-2014-0001LMN #framework #invariant #learning #named #robust: ICE: A Robust Framework for Learning Invariants (PG, CL, PM, DN), pp. 69–87.
CAV-2014-HeizmannHP #analysis #learning #source code #termination: Termination Analysis by Learning Terminating Programs (MH, JH, AP), pp. 797–813.
SMT-2014-KorovinKS #learning #towards: Towards Conflict-Driven Learning for Virtual Substitution (KK, MK, TS), p. 71.
ASE-2013-DietrichCS #effectiveness #learning #query #requirements #retrieval: Learning effective query transformations for enhanced requirements trace retrieval (TD, JCH, YS), pp. 586–591.
ASE-2013-GuoCASW #approach #learning #performance #predict #statistics #variability: Variability-aware performance prediction: A statistical learning approach (JG, KC, SA, NS, AW), pp. 301–311.
ASE-2013-Xiao0LLS #learning #named #type system: TzuYu: Learning stateful typestates (HX, JS, YL, SWL, CS), pp. 432–442.
CASE-2013-LiX #adaptation #learning: Off-line learning based adaptive dispatching rule for semiconductor wafer fabrication facility (LL, HX), pp. 1028–1033.
CASE-2013-OFlahertyE #bound #learning #sequence: Learning to locomote: Action sequences and switching boundaries (RO, ME), pp. 7–12.
CASE-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.
DAC-2013-LiuC #on the #synthesis: On learning-based methods for design-space exploration with high-level synthesis (HYL, LPC), p. 7.
DAC-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.
DATE-2013-DeOrioLBB #debugging #detection #machine learning: Machine learning-based anomaly detection for post-silicon bug diagnosis (AD, QL, MB, VB), pp. 491–496.
DATE-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.
DocEng-2013-DoTT #documentation #taxonomy #using: Document noise removal using sparse representations over learned dictionary (THD, ST, ORT), pp. 161–168.
DocEng-2013-Esposito #documentation #machine learning: Symbolic machine learning methods for historical document processing (FE), pp. 1–2.
ICDAR-2013-AgarwalGC #learning: Greedy Search for Active Learning of OCR (AA, RG, SC), pp. 837–841.
ICDAR-2013-BougueliaBB #approach #classification #documentation #learning: A Stream-Based Semi-supervised Active Learning Approach for Document Classification (MRB, YB, AB), pp. 611–615.
ICDAR-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.
ICDAR-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.
ICDAR-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.
ICDAR-2013-NguyenCBO #image #interactive #learning: Interactive Knowledge Learning for Ancient Images (NVN, MC, AB, JMO), pp. 300–304.
ICDAR-2013-PuriST #learning #network: Bayesian Network Structure Learning and Inference Methods for Handwriting (MP, SNS, YT), pp. 1320–1324.
ICDAR-2013-SchambachR #learning #network #sequence: Stabilize Sequence Learning with Recurrent Neural Networks by Forced Alignment (MPS, SFR), pp. 1270–1274.
ICDAR-2013-SuL #learning #recognition: Discriminative Weighting and Subspace Learning for Ensemble Symbol Recognition (FS, TL), pp. 1088–1092.
ICDAR-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.
ICDAR-2013-TeradaHFU #detection #on the: On the Possibility of Structure Learning-Based Scene Character Detector (YT, RH, YF, SU), pp. 472–476.
ICDAR-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.
ICDAR-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.
ICDAR-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.
ICDAR-2013-Zhu0N #learning #recognition: Sub-structure Learning Based Handwritten Chinese Text Recognition (YZ, JS, SN), pp. 295–299.
PODS-2013-AbouziedAPHS #learning #quantifier #query #verification: Learning and verifying quantified boolean queries by example (AA, DA, CHP, JMH, AS), pp. 49–60.
SIGMOD-2013-CondieMPW #big data #machine learning: Machine learning for big data (TC, PM, NP, MW), pp. 939–942.
SIGMOD-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.
VLDB-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.
VLDB-2013-BrunatoB #learning #optimisation: Learning and Intelligent Optimization (LION): One Ring to Rule Them All (MB, RB), pp. 1176–1177.
VLDB-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.
VLDB-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.
CSEET-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.
CSEET-2013-Georgas #composition #design #education #learning #towards: Toward infusing modular and reflective design learning throughout the curriculum (JCG), pp. 274–278.
CSEET-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.
CSEET-2013-StejskalS #learning #testing: Test-driven learning in high school computer science (RS, HPS), pp. 289–293.
CSEET-2013-Vallino #question #re-engineering #student #what: What should students learn in their first (and often only) software engineering course? (JV), pp. 335–337.
ITiCSE-2013-Alshaigy #development #education #interactive #learning #programming language #python: Development of an interactive learning tool to teach python programming language (BA), p. 344.
ITiCSE-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.
ITiCSE-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.
ITiCSE-2013-FernandesCB #learning: A pilot project on non-conventional learning (SF, AC, LSB), p. 346.
ITiCSE-2013-German #learning: Jump-starting team-based learning in the computer science classroom (DAG), p. 323.
ITiCSE-2013-GorlatovaSKKZ #learning #research #scalability: Project-based learning within a large-scale interdisciplinary research effort (MG, JS, PRK, IK, GZ), pp. 207–212.
ITiCSE-2013-HawthorneC #learning #source code: ACM core IT learning outcomes for associate-degree programs (EKH, RDC), p. 357.
ITiCSE-2013-JalilPWL #design #interactive #learning #taxonomy: Design eye: an interactive learning environment based on the solo taxonomy (SAJ, BP, IW, ALR), pp. 22–27.
ITiCSE-2013-JohnsonCH #contest #development #game studies #learning: Learning elsewhere: tales from an extracurricular game development competition (CJ, AC, SH), pp. 70–75.
ITiCSE-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.
ITiCSE-2013-MellodgeR #arduino #case study #experience #framework #learning #student #using: Using the arduino platform to enhance student learning experiences (PM, IR), p. 338.
ITiCSE-2013-Paule-RuizGPG #evaluation #framework #interactive #learning: Voice interactive learning: a framework and evaluation (MPPR, VMÁG, JRPP, MRG), pp. 34–39.
ITiCSE-2013-QianYGBT #authentication #learning #mobile #network #security: Mobile device based authentic learning for computer network and security (KQ, MY, MG, PB, LT), p. 335.
ITiCSE-2013-ReedZ #framework #learning: A hierarchical framework for mapping and quantitatively assessing program and learning outcomes (JR, HZ), pp. 52–57.
ITiCSE-2013-RowanD #bibliography #learning #mobile #using: A systematic literature review on using mobile computing as a learning intervention (MR, JD), p. 339.
ITiCSE-2013-Sanchez-Nielsen #learning #multi #student: Producing multimedia pills to stimulate student learning and engagement (ESN), pp. 165–170.
ITiCSE-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.
ITiCSE-2013-ShiQC #adaptation #design #personalisation #social: Designing social personalized adaptive e-learning (LS, DAQ, AIC), p. 341.
ITiCSE-2013-VihavainenVLP #learning #student #using: Scaffolding students’ learning using test my code (AV, TV, ML, MP), pp. 117–122.
ITiCSE-2013-Wildsmith #learning #named: Kinetic: a learning environment within business (CW), p. 3.
TACAS-2013-ChenW #algorithm #learning #library #named: BULL: A Library for Learning Algorithms of Boolean Functions (YFC, BYW), pp. 537–542.
TACAS-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.
CSMR-2013-MinelliL #lessons learnt #mobile: Software Analytics for Mobile Applications-Insights & Lessons Learned (RM, ML), pp. 144–153.
CSMR-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.
ICSM-2013-FontanaZMM #approach #detection #machine learning #smell #towards: Code Smell Detection: Towards a Machine Learning-Based Approach (FAF, MZ, AM, MM), pp. 396–399.
ICSM-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.
ICSM-2013-Perez #design #lessons learnt #refactoring #smell #summary: Refactoring Planning for Design Smell Correction: Summary, Opportunities and Lessons Learned (JP), pp. 572–577.
ICSM-2013-SemenenkoDS #image #machine learning #named #testing: Browserbite: Accurate Cross-Browser Testing via Machine Learning over Image Features (NS, MD, TS), pp. 528–531.
ICSM-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.
ICSM-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.
WCRE-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.
WCRE-2013-MontandonBFV #api #framework #lessons learnt: Documenting APIs with examples: Lessons learned with the APIMiner platform (JEM, HB, DF, MTV), pp. 401–408.
SAS-2013-0001GHAN #concept #geometry #learning #verification: Verification as Learning Geometric Concepts (RS, SG, BH, AA, AVN), pp. 388–411.
STOC-2013-BrakerskiLPRS #fault #learning: Classical hardness of learning with errors (ZB, AL, CP, OR, DS), pp. 575–584.
DLT-2013-BolligHLM #approach #automaton #learning: A Fresh Approach to Learning Register Automata (BB, PH, ML, BM), pp. 118–130.
ICALP-v2-2013-FuscoPP #learning #performance: Learning a Ring Cheaply and Fast (EGF, AP, RP), pp. 557–568.
LATA-2013-BjorklundFK #automaton #learning: MAT Learning of Universal Automata (JB, HF, AK), pp. 141–152.
GT-VMT-2013-AlshanqitiHK #graph transformation #learning: Learning Minimal and Maximal Rules from Observations of Graph Transformations (AMA, RH, TAK).
CHI-2013-AndersonB #gesture #learning #performance: Learning and performance with gesture guides (FA, WFB), pp. 1109–1118.
CHI-2013-EdgeCW #learning #named: SpatialEase: learning language through body motion (DE, KYC, MW), pp. 469–472.
CHI-2013-HarpsteadMA #data analysis #education #game studies #learning: In search of learning: facilitating data analysis in educational games (EH, BAM, VA), pp. 79–88.
CHI-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.
CHI-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.
CHI-2013-SzafirM #adaptation #bibliography #learning #named: ARTFul: adaptive review technology for flipped learning (DS, BM), pp. 1001–1010.
CSCW-2013-KowY #community #learning: Media technologies and learning in the starcraft esport community (YMK, TY), pp. 387–398.
CSCW-2013-LinF #learning #network: Opportunities via extended networks for teens’ informal learning (PL, SDF), pp. 1341–1352.
DHM-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.
DUXU-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.
DUXU-CXC-2013-ChoensawatSKH #education #learning: Desirability of a Teaching and Learning Tool for Thai Dance Body Motion (WC, KS, CK, KH), pp. 171–179.
DUXU-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.
DUXU-CXC-2013-MarchettiB #game studies #learning: Setting Conditions for Learning: Mediated Play and Socio-material Dialogue (EM, EPB), pp. 238–246.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
DUXU-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.
HCI-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.
HCI-AS-2013-AndujarEGM #learning: Evaluating Engagement Physiologically and Knowledge Retention Subjectively through Two Different Learning Techniques (MA, JIE, JEG, PM), pp. 335–342.
HCI-AS-2013-BitontoLRR #collaboration #process #recommendation: Recommendation of Collaborative Activities in E-learning Environments (PDB, ML, TR, VR), pp. 484–492.
HCI-AS-2013-CharoenpitO #biology #using: A New E-learning System Focusing on Emotional Aspect Using Biological Signals (SC, MO), pp. 343–350.
HCI-AS-2013-EskildsenR #challenge #integration #learning: Challenges for Contextualizing Language Learning — Supporting Cultural Integration (SE, MR), pp. 361–369.
HCI-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.
HCI-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.
HCI-AS-2013-HarunBON #learning #using: Refining Rules Learning Using Evolutionary PD (AFH, SB, CO, NLMN), pp. 376–385.
HCI-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.
HCI-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.
HCI-AS-2013-LimaRSBSO #learning: Innovation in Learning — The Use of Avatar for Sign Language (TL, MSR, TAS, AB, ES, HSdO), pp. 428–433.
HCI-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.
HCI-AS-2013-MarsicoST #framework #personalisation: A Framework to Support Social-Collaborative Personalized e-Learning (MDM, AS, MT), pp. 351–360.
HCI-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.
HCI-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.
HCI-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.
HCI-AS-2013-TakanoS #learning: Nature Sound Ensemble Learning in Narrative-Episode Creation with Pictures (KT, SS), pp. 493–502.
HCI-AS-2013-TogawaK #framework: Private Cloud Cooperation Framework for Reducing the Earthquake Damage on e-Learning Environment (ST, KK), pp. 503–510.
HCI-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.
HCI-IMT-2013-DruryPKL #design #lessons learnt #visualisation: Decision Space Visualization: Lessons Learned and Design Principles (JLD, MSP, GLK, YL), pp. 658–667.
HCI-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.
HCI-UC-2013-StarySF #interactive #learning: Agility Based on Stakeholder Interaction — Blending Organizational Learning with Interactive BPM (CS, WS, AF), pp. 456–465.
HIMI-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.
HIMI-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.
HIMI-HSM-2013-SaitohI #detection #learning #using #visualisation: Visualization of Anomaly Data Using Peculiarity Detection on Learning Vector Quantization (FS, SI), pp. 181–188.
HIMI-LCCB-2013-Canter #hybrid #student: A Hybrid Model for an E-learning System Which Develops Metacognitive Skills at Students (MC), pp. 9–15.
HIMI-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.
HIMI-LCCB-2013-HallLS #assessment #evaluation #learning #tool support: Psychophysiological Assessment Tools for Evaluation of Learning Technologies (RHH, NSL, HS), pp. 33–42.
HIMI-LCCB-2013-HayashiON #collaboration #interactive #learning: An Experimental Environment for Analyzing Collaborative Learning Interaction (YH, YO, YIN), pp. 43–52.
HIMI-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.
HIMI-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.
HIMI-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.
HIMI-LCCB-2013-YamamotoKYMH #learning #online #problem: Learning by Problem-Posing with Online Connected Media Tablets (SY, TK, YY, KM, TH), pp. 165–174.
HIMI-LCCB-2013-YuL #approach #feedback #mining: Exploring User Feedback of a E-Learning System: A Text Mining Approach (WBY, RL), pp. 182–191.
OCSC-2013-Eustace #learning #network: Building and Sustaining a Lifelong Adult Learning Network (KE), pp. 260–268.
OCSC-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.
VISSOFT-2013-Wijk #case study #experience #lessons learnt #visualisation: Keynote talk: Information visualization: Experiences and lessons learned (JJvW), p. 1.
EDOC-2013-Swenson #design #learning: Designing for an Innovative Learning Organization (KDS), pp. 209–213.
ICEIS-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.
ICEIS-v2-2013-EomA #testing: Developing and Testing a Model to Understand Relationships between e-Learning Outcomes and Human Factors (SBE, NJA), pp. 361–370.
ICEIS-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.
ICEIS-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.
ICEIS-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.
ICEIS-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.
ICEIS-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.
CIKM-2013-BaragliaMNS #learning #named #predict: LearNext: learning to predict tourists movements (RB, CIM, FMN, FS), pp. 751–756.
CIKM-2013-CeccarelliLOPT #learning #metric: Learning relatedness measures for entity linking (DC, CL, SO, RP, ST), pp. 139–148.
CIKM-2013-ChengCLWAC #data type #learning #multi: Feedback-driven multiclass active learning for data streams (YC, ZC, LL, JW, AA, ANC), pp. 1311–1320.
CIKM-2013-ChenW #classification #learning #scalability: Cost-sensitive learning for large-scale hierarchical classification (JC, DW), pp. 1351–1360.
CIKM-2013-FangZ #feature model #learning #multi: Discriminative feature selection for multi-view cross-domain learning (ZF, Z(Z), pp. 1321–1330.
CIKM-2013-Guestrin #machine learning #scalability #usability: Usability in machine learning at scale with graphlab (CG), pp. 5–6.
CIKM-2013-HashemiNB #approach #learning #network #retrieval #topic: Expertise retrieval in bibliographic network: a topic dominance learning approach (SHH, MN, HB), pp. 1117–1126.
CIKM-2013-KamathC #learning #predict #what: Spatio-temporal meme prediction: learning what hashtags will be popular where (KYK, JC), pp. 1341–1350.
ECIR-2013-DangBC #information retrieval #learning #rank: Two-Stage Learning to Rank for Information Retrieval (VD, MB, WBC), pp. 423–434.
ECIR-2013-JuMJ #classification #learning #rank: Learning to Rank from Structures in Hierarchical Text Classification (QJ, AM, RJ), pp. 183–194.
ECIR-2013-NguyenTT #classification #learning #rank #using: Folktale Classification Using Learning to Rank (DN, DT, MT), pp. 195–206.
ICML-c1-2013-0005LSL #feature model #learning #modelling #online: Online Feature Selection for Model-based Reinforcement Learning (TTN, ZL, TS, TYL), pp. 498–506.
ICML-c1-2013-AbernethyAKD #learning #problem #scalability: Large-Scale Bandit Problems and KWIK Learning (JA, KA, MK, MD), pp. 588–596.
ICML-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.
ICML-c1-2013-AnandkumarHJK #learning #linear #network: Learning Linear Bayesian Networks with Latent Variables (AA, DH, AJ, SK), pp. 249–257.
ICML-c1-2013-BalcanBEL #learning #performance: Efficient Semi-supervised and Active Learning of Disjunctions (NB, CB, SE, YL), pp. 633–641.
ICML-c1-2013-BootsG #approach #learning: A Spectral Learning Approach to Range-Only SLAM (BB, GJG), pp. 19–26.
ICML-c1-2013-ChenK #adaptation #learning #optimisation: Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization (YC, AK), pp. 160–168.
ICML-c1-2013-CotterSS #learning: Learning Optimally Sparse Support Vector Machines (AC, SSS, NS), pp. 266–274.
ICML-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.
ICML-c1-2013-GolubCY #learning: Learning an Internal Dynamics Model from Control Demonstration (MG, SC, BY), pp. 606–614.
ICML-c1-2013-GonenSS #approach #learning #performance: Efficient Active Learning of Halfspaces: an Aggressive Approach (AG, SS, SSS), pp. 480–488.
ICML-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.
ICML-c1-2013-KadriGP #approach #kernel #learning: A Generalized Kernel Approach to Structured Output Learning (HK, MG, PP), pp. 471–479.
ICML-c1-2013-KarbasiSS #learning: Iterative Learning and Denoising in Convolutional Neural Associative Memories (AK, AHS, AS), pp. 445–453.
ICML-c1-2013-KumarB #bound #graph #learning: Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs (KSSK, FRB), pp. 525–533.
ICML-c1-2013-LiLSHD #generative #learning #using: Learning Hash Functions Using Column Generation (XL, GL, CS, AvdH, ARD), pp. 142–150.
ICML-c1-2013-LimLM #learning #metric #robust: Robust Structural Metric Learning (DL, GRGL, BM), pp. 615–623.
ICML-c1-2013-MaatenCTW #learning: Learning with Marginalized Corrupted Features (LvdM, MC, ST, KQW), pp. 410–418.
ICML-c1-2013-MaillardNOR #bound #learning #representation: Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning (OAM, PN, RO, DR), pp. 543–551.
ICML-c1-2013-MenonTGLK #framework #machine learning #programming: A Machine Learning Framework for Programming by Example (AKM, OT, SG, BWL, AK), pp. 187–195.
ICML-c1-2013-RuvoloE #algorithm #learning #named #performance: ELLA: An Efficient Lifelong Learning Algorithm (PR, EE), pp. 507–515.
ICML-c1-2013-ZuluagaSKP #learning #multi #optimisation: Active Learning for Multi-Objective Optimization (MZ, GS, AK, MP), pp. 462–470.
ICML-c2-2013-GaneshapillaiGL #learning: Learning Connections in Financial Time Series (GG, JVG, AL), pp. 109–117.
ICML-c2-2013-GolovinSMY #learning #ram #scalability: Large-Scale Learning with Less RAM via Randomization (DG, DS, HBM, MY), pp. 325–333.
ICML-c2-2013-KrummenacherOB #learning #multi: Ellipsoidal Multiple Instance Learning (GK, CSO, JMB), pp. 73–81.
ICML-c2-2013-MaurerPR #learning #multi: Sparse coding for multitask and transfer learning (AM, MP, BRP), pp. 343–351.
ICML-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.
ICML-c2-2013-MinhBM #framework #learning #multi: A unifying framework for vector-valued manifold regularization and multi-view learning (HQM, LB, VM), pp. 100–108.
ICML-c2-2013-RanganathWBX #adaptation #learning #probability: An Adaptive Learning Rate for Stochastic Variational Inference (RR, CW, DMB, EPX), pp. 298–306.
ICML-c2-2013-SohnZLL #learning: Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines (KS, GZ, CL, HL), pp. 217–225.
ICML-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.
ICML-c2-2013-TranPV #learning #multi: Thurstonian Boltzmann Machines: Learning from Multiple Inequalities (TT, DQP, SV), pp. 46–54.
ICML-c2-2013-YangH #classification #learning: Activized Learning with Uniform Classification Noise (LY, SH), pp. 370–378.
ICML-c3-2013-0002T #kernel #learning: Differentially Private Learning with Kernels (PJ, AT), pp. 118–126.
ICML-c3-2013-AlmingolML #behaviour #learning #multi: Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space (JA, LM, ML), pp. 136–144.
ICML-c3-2013-BalasubramanianYL #learning: Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations (KB, KY, GL), pp. 289–297.
ICML-c3-2013-BalcanBM #learning #ontology: Exploiting Ontology Structures and Unlabeled Data for Learning (NB, AB, YM), pp. 1112–1120.
ICML-c3-2013-BellemareVB #learning #recursion: Bayesian Learning of Recursively Factored Environments (MGB, JV, MB), pp. 1211–1219.
ICML-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.
ICML-c3-2013-ChattopadhyayFDPY #learning: Joint Transfer and Batch-mode Active Learning (RC, WF, ID, SP, JY), pp. 253–261.
ICML-c3-2013-Cheng #learning #similarity: Riemannian Similarity Learning (LC), pp. 540–548.
ICML-c3-2013-CoatesHWWCN #learning #off the shelf: Deep learning with COTS HPC systems (AC, BH, TW, DJW, BCC, AYN), pp. 1337–1345.
ICML-c3-2013-DalalyanHMS #learning #modelling #programming: Learning Heteroscedastic Models by Convex Programming under Group Sparsity (ASD, MH, KM, JS), pp. 379–387.
ICML-c3-2013-DimitrakakisT #learning: ABC Reinforcement Learning (CD, NT), pp. 684–692.
ICML-c3-2013-GensD #learning #network: Learning the Structure of Sum-Product Networks (RG, PMD), pp. 873–880.
ICML-c3-2013-GittensM #machine learning #scalability: Revisiting the Nystrom method for improved large-scale machine learning (AG, MWM), pp. 567–575.
ICML-c3-2013-GuptaPV #approach #learning #multi #parametricity: Factorial Multi-Task Learning : A Bayesian Nonparametric Approach (SKG, DQP, SV), pp. 657–665.
ICML-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.
ICML-c3-2013-HoXV #learning #on the #taxonomy: On A Nonlinear Generalization of Sparse Coding and Dictionary Learning (JH, YX, BCV), pp. 1480–1488.
ICML-c3-2013-HuangS #learning #markov #modelling: Spectral Learning of Hidden Markov Models from Dynamic and Static Data (TKH, JGS), pp. 630–638.
ICML-c3-2013-JancsaryNR #learning #predict: Learning Convex QP Relaxations for Structured Prediction (JJ, SN, CR), pp. 915–923.
ICML-c3-2013-JoseGAV #kernel #learning #performance #predict: Local Deep Kernel Learning for Efficient Non-linear SVM Prediction (CJ, PG, PA, MV), pp. 486–494.
ICML-c3-2013-JoulaniGS #feedback #learning #online: Online Learning under Delayed Feedback (PJ, AG, CS), pp. 1453–1461.
ICML-c3-2013-JunZSR #learning: Learning from Human-Generated Lists (KSJ, X(Z, BS, TTR), pp. 181–189.
ICML-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.
ICML-c3-2013-KontorovichNW #learning #on the: On learning parametric-output HMMs (AK, BN, RW), pp. 702–710.
ICML-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.
ICML-c3-2013-KraehenbuehlK #convergence #learning #parametricity #random: Parameter Learning and Convergent Inference for Dense Random Fields (PK, VK), pp. 513–521.
ICML-c3-2013-KuzborskijO #learning: Stability and Hypothesis Transfer Learning (IK, FO), pp. 942–950.
ICML-c3-2013-LattimoreHS #learning: The Sample-Complexity of General Reinforcement Learning (TL, MH, PS), pp. 28–36.
ICML-c3-2013-MalioutovV #learning: Exact Rule Learning via Boolean Compressed Sensing (DMM, KRV), pp. 765–773.
ICML-c3-2013-MemisevicE #invariant #learning #problem: Learning invariant features by harnessing the aperture problem (RM, GE), pp. 100–108.
ICML-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.
ICML-c3-2013-RamanJSS #learning: Stable Coactive Learning via Perturbation (KR, TJ, PS, TS), pp. 837–845.
ICML-c3-2013-Romera-ParedesABP #learning #multi: Multilinear Multitask Learning (BRP, HA, NBB, MP), pp. 1444–1452.
ICML-c3-2013-RossZYDB #learning #policy #predict: Learning Policies for Contextual Submodular Prediction (SR, JZ, YY, DD, DB), pp. 1364–1372.
ICML-c3-2013-SchaulZL #learning: No more pesky learning rates (TS, SZ, YL), pp. 343–351.
ICML-c3-2013-SilverNBWM #concurrent #interactive #learning: Concurrent Reinforcement Learning from Customer Interactions (DS, LN, DB, SW, JM), pp. 924–932.
ICML-c3-2013-SimsekliCY #learning #matrix #modelling: Learning the β-Divergence in Tweedie Compound Poisson Matrix Factorization Models (US, ATC, YKY), pp. 1409–1417.
ICML-c3-2013-SodomkaHLG #game studies #learning #named #probability: Coco-Q: Learning in Stochastic Games with Side Payments (ES, EH, MLL, AG), pp. 1471–1479.
ICML-c3-2013-SutskeverMDH #learning #on the: On the importance of initialization and momentum in deep learning (IS, JM, GED, GEH), pp. 1139–1147.
ICML-c3-2013-TarlowSCSZ #learning #probability: Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning (DT, KS, LC, IS, RSZ), pp. 199–207.
ICML-c3-2013-WangNH #learning #robust #self: Robust and Discriminative Self-Taught Learning (HW, FN, HH), pp. 298–306.
ICML-c3-2013-WangNH13a #clustering #learning #multi: Multi-View Clustering and Feature Learning via Structured Sparsity (HW, FN, HH), pp. 352–360.
ICML-c3-2013-WangWBLT #learning #multi #taxonomy: Max-Margin Multiple-Instance Dictionary Learning (XW, BW, XB, WL, ZT), pp. 846–854.
ICML-c3-2013-XuKHW #learning #representation: Anytime Representation Learning (ZEX, MJK, GH, KQW), pp. 1076–1084.
ICML-c3-2013-YangLZ #learning #matrix #multi: Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model (MY, YL, ZZ), pp. 423–431.
ICML-c3-2013-YuLKJC #learning: ∝SVM for Learning with Label Proportions (FXY, DL, SK, TJ, SFC), pp. 504–512.
ICML-c3-2013-ZemelWSPD #learning: Learning Fair Representations (RSZ, YW, KS, TP, CD), pp. 325–333.
ICML-c3-2013-ZhangYJLH #bound #kernel #learning #online: Online Kernel Learning with a Near Optimal Sparsity Bound (LZ, JY, RJ, ML, XH), pp. 621–629.
ICML-c3-2013-ZhouZS #kernel #learning #multi #process: Learning Triggering Kernels for Multi-dimensional Hawkes Processes (KZ, HZ, LS), pp. 1301–1309.
ICML-c3-2013-ZweigW #learning: Hierarchical Regularization Cascade for Joint Learning (AZ, DW), pp. 37–45.
KDD-2013-BahadoriLX #learning #performance #probability #process: Fast structure learning in generalized stochastic processes with latent factors (MTB, YL, EPX), pp. 284–292.
KDD-2013-ChakrabartiH #learning #scalability #social: Speeding up large-scale learning with a social prior (DC, RH), pp. 650–658.
KDD-2013-ChenHKB #learning #named: DTW-D: time series semi-supervised learning from a single example (YC, BH, EJK, GEAPAB), pp. 383–391.
KDD-2013-DasMGW #learning: Learning to question: leveraging user preferences for shopping advice (MD, GDFM, AG, IW), pp. 203–211.
KDD-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.
KDD-2013-GeGLZ #estimation #learning #multi: Multi-source deep learning for information trustworthiness estimation (LG, JG, XL, AZ), pp. 766–774.
KDD-2013-GilpinED #algorithm #framework #learning: Guided learning for role discovery (GLRD): framework, algorithms, and applications (SG, TER, IND), pp. 113–121.
KDD-2013-HaoCZ0RK #learning #towards: Towards never-ending learning from time series streams (YH, YC, JZ, BH, TR, EJK), pp. 874–882.
KDD-2013-Howard #learning: The business impact of deep learning (JH), p. 1135.
KDD-2013-KongY #automation #classification #distance #learning: Discriminant malware distance learning on structural information for automated malware classification (DK, GY), pp. 1357–1365.
KDD-2013-KutzkovBBG #learning #named: STRIP: stream learning of influence probabilities (KK, AB, FB, AG), pp. 275–283.
KDD-2013-LinWHY #information management #learning #modelling #social: Extracting social events for learning better information diffusion models (SL, FW, QH, PSY), pp. 365–373.
KDD-2013-LiuFYX #learning #recommendation: Learning geographical preferences for point-of-interest recommendation (BL, YF, ZY, HX), pp. 1043–1051.
KDD-2013-MorenoNK #graph #learning #modelling: Learning mixed kronecker product graph models with simulated method of moments (SM, JN, SK), pp. 1052–1060.
KDD-2013-SutherlandPS #learning #matrix #rank: Active learning and search on low-rank matrices (DJS, BP, JGS), pp. 212–220.
KDD-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.
KDD-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.
KDD-2013-WangY #learning #query: Querying discriminative and representative samples for batch mode active learning (ZW, JY), pp. 158–166.
KDD-2013-Wright #data analysis #learning #optimisation: Optimization in learning and data analysis (SJW), p. 3.
KDD-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.
KDD-2013-ZhangHL #learning #multi #named: MI2LS: multi-instance learning from multiple informationsources (DZ, JH, RDL), pp. 149–157.
KDD-2013-ZhaoH #detection #learning #online: Cost-sensitive online active learning with application to malicious URL detection (PZ, SCHH), pp. 919–927.
KDD-2013-ZhaoYNG #framework #learning #twitter: A transfer learning based framework of crowd-selection on twitter (ZZ, DY, WN, SG), pp. 1514–1517.
KDIR-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.
KDIR-KMIS-2013-BerkaniN #collaboration #learning #recommendation #semantics: Semantic Collaborative Filtering for Learning Objects Recommendation (LB, ON), pp. 52–63.
KDIR-KMIS-2013-CastellanoS: Developing Innovative e-Learning Solutions (MC, FAS), pp. 484–489.
KDIR-KMIS-2013-Dessne #learning: Learning in an Organisation — Exploring the Nature of Relationships (KD), pp. 496–501.
KDIR-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.
KDIR-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.
KDIR-KMIS-2013-SaxenaBW #composition #learning: A Cognitive Reference based Model for Learning Compositional Hierarchies with Whole-composite Tags (ABS, AB, AW), pp. 119–127.
KEOD-2013-WohlgenanntBS #automation #evolution #learning #ontology #prototype: A Prototype for Automating Ontology Learning and Ontology Evolution (GW, SB, MS), pp. 407–412.
MLDM-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.
MLDM-2013-ElGibreenA #learning #multi #product line: Multi Model Transfer Learning with RULES Family (HE, MSA), pp. 42–56.
MLDM-2013-GopalakrishnaOLL #algorithm #machine learning #metric: Relevance as a Metric for Evaluating Machine Learning Algorithms (AKG, TO, AL, JJL), pp. 195–208.
MLDM-2013-KoharaS #learning #self: Typhoon Damage Scale Forecasting with Self-Organizing Maps Trained by Selective Presentation Learning (KK, IS), pp. 16–26.
MLDM-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.
MLDM-2013-Suthaharan #big data #classification #network: A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion (SS), pp. 296–310.
RecSys-2013-HuY #learning #process #recommendation: Interview process learning for top-n recommendation (FH, YY), pp. 331–334.
RecSys-2013-KaratzoglouBS #learning #rank #recommendation: Learning to rank for recommender systems (AK, LB, YS), pp. 493–494.
RecSys-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.
RecSys-2013-SharmaY #community #learning #recommendation: Pairwise learning in recommendation: experiments with community recommendation on linkedin (AS, BY), pp. 193–200.
RecSys-2013-WestonYW #learning #rank #recommendation #statistics: Learning to rank recommendations with the k-order statistic loss (JW, HY, RJW), pp. 245–248.
SEKE-2013-BarbosaFNM #architecture #learning #towards: Towards the Establishment of a Reference Architecture for Developing Learning Environments (EFB, MLF, EYN, JCM), pp. 350–355.
SEKE-2013-CarrerasZO #machine learning: A Machine Learning Based File Archival Tool (S) (RC, DZ, JO), pp. 73–76.
SEKE-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.
SIGIR-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.
SIGIR-2013-LimsopathamMO #learning: Learning to combine representations for medical records search (NL, CM, IO), pp. 833–836.
SIGIR-2013-Moschitti #kernel #learning #rank #semantics: Kernel-based learning to rank with syntactic and semantic structures (AM), p. 1128.
SIGIR-2013-Shokouhi #learning #personalisation #query: Learning to personalize query auto-completion (MS), pp. 103–112.
SIGIR-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.
SIGIR-2013-ZhangWYW #learning #network #predict: Learning latent friendship propagation networks with interest awareness for link prediction (JZ, CW, PSY, JW), pp. 63–72.
ICMT-2013-FaunesSB #approach #model transformation: Genetic-Programming Approach to Learn Model Transformation Rules from Examples (MF, HAS, MB), pp. 17–32.
OOPSLA-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.
POPL-2013-BotincanB #learning #specification: Sigma*: symbolic learning of input-output specifications (MB, DB), pp. 443–456.
POPL-2013-DSilvaHK #learning: Abstract conflict driven learning (VD, LH, DK), pp. 143–154.
RE-2013-ShiWL #evolution #learning #predict: Learning from evolution history to predict future requirement changes (LS, QW, ML), pp. 135–144.
RE-2013-SultanovH #learning #requirements: Application of reinforcement learning to requirements engineering: requirements tracing (HS, JHH), pp. 52–61.
REFSQ-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.
SAC-2013-AkritidisB #algorithm #classification #machine learning #research: A supervised machine learning classification algorithm for research articles (LA, PB), pp. 115–120.
SAC-2013-BerralGT #automation #machine learning: Empowering automatic data-center management with machine learning (JLB, RG, JT), pp. 170–172.
SAC-2013-BlondelSU #classification #constraints #learning #using: Learning non-linear classifiers with a sparsity constraint using L1 regularization (MB, KS, KU), pp. 167–169.
SAC-2013-FilhoB #learning #mobile #requirements: A requirements catalog for mobile learning environments (NFDF, EFB), pp. 1266–1271.
SAC-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.
SAC-2013-LommatzschKA #hybrid #learning #modelling #recommendation #semantics: Learning hybrid recommender models for heterogeneous semantic data (AL, BK, SA), pp. 275–276.
SAC-2013-SeelandKP #graph #kernel #learning: Model selection based product kernel learning for regression on graphs (MS, SK, BP), pp. 136–143.
SAC-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.
ICSE-2013-CotroneoPR #testing: A learning-based method for combining testing techniques (DC, RP, SR), pp. 142–151.
ICSE-2013-Jonsson #machine learning #performance #scalability #using: Increasing anomaly handling efficiency in large organizations using applied machine learning (LJ), pp. 1361–1364.
ICSE-2013-KimNSK #automation #generative: Automatic patch generation learned from human-written patches (DK, JN, JS, SK), pp. 802–811.
ICSE-2013-MengKM #learning #named: LASE: locating and applying systematic edits by learning from examples (NM, MK, KSM), pp. 502–511.
ICSE-2013-NamPK #fault #learning: Transfer defect learning (JN, SJP, SK), pp. 382–391.
ICSE-2013-SykesCMKRI #adaptation #learning #modelling: Learning revised models for planning in adaptive systems (DS, DC, JM, JK, AR, KI), pp. 63–71.
ICSE-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.
CC-2013-MooreC #automation #generative #machine learning #policy #using: Automatic Generation of Program Affinity Policies Using Machine Learning (RWM, BRC), pp. 184–203.
CGO-2013-KulkarniCWS #automation #heuristic #machine learning #using: Automatic construction of inlining heuristics using machine learning (SK, JC, CW, DS), p. 12.
CAV-2013-0001LMN #data type #invariant #learning #linear #quantifier: Learning Universally Quantified Invariants of Linear Data Structures (PG, CL, PM, DN), pp. 813–829.
CAV-2013-ChagantyLNR #learning #relational #smt #using: Combining Relational Learning with SMT Solvers Using CEGAR (ATC, AL, AVN, SKR), pp. 447–462.
ICST-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.
ICST-2013-MeinkeS #named #testing: LBTest: A Learning-Based Testing Tool for Reactive Systems (KM, MAS), pp. 447–454.
ICTSS-2013-FengLMNSW #case study #testing: Case Studies in Learning-Based Testing (LF, SL, KM, FN, MAS, PYHW), pp. 164–179.
ISSTA-2013-HowarGR #analysis #generative #hybrid #interface #learning: Hybrid learning: interface generation through static, dynamic, and symbolic analysis (FH, DG, ZR), pp. 268–279.
ISSTA-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.
SAT-2013-Ben-Ari #education #named #satisfiability: LearnSAT: A SAT Solver for Education (MBA), pp. 403–407.
SAT-2013-Johannsen #exponential #learning #proving: Exponential Separations in a Hierarchy of Clause Learning Proof Systems (JJ), pp. 40–51.
SAT-2013-LonsingEG #learning #performance #pseudo #quantifier: Efficient Clause Learning for Quantified Boolean Formulas via QBF Pseudo Unit Propagation (FL, UE, AVG), pp. 100–115.
CBSE-2012-AbateCTZ #component #future of #learning #repository: Learning from the future of component repositories (PA, RDC, RT, SZ), pp. 51–60.
ASE-2012-LuCC #fault #learning #predict #reduction #using: Software defect prediction using semi-supervised learning with dimension reduction (HL, BC, MC), pp. 314–317.
CASE-2012-AnKP #learning #modelling #process: Grasp motion learning with Gaussian Process Dynamic Models (BA, HK, FCP), pp. 1114–1119.
CASE-2012-YamamotoD #interface #learning: Robot interface learning user-defined voice instructions (DY, MD), pp. 926–929.
DAC-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.
DATE-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.
DocEng-2012-MoulderM #how #layout #learning: Learning how to trade off aesthetic criteria in layout (PM, KM), pp. 33–36.
HT-2012-SchofeggerKSG #behaviour #learning #social: Learning user characteristics from social tagging behavior (KS, CK, PS, MG), pp. 207–212.
SIGMOD-2012-AbiteboulAMS #learning #xml: Auto-completion learning for XML (SA, YA, TM, PS), pp. 669–672.
SIGMOD-2012-LinK #machine learning #scalability #twitter: Large-scale machine learning at twitter (JL, AK), pp. 793–804.
VLDB-2012-IseleB #learning #programming #search-based #using: Learning Expressive Linkage Rules using Genetic Programming (RI, CB), pp. 1638–1649.
VLDB-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.
VLDB-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.
VLDB-2012-SinghG #learning #semantics #string: Learning Semantic String Transformations from Examples (RS, SG), pp. 740–751.
CSEET-2012-AroraG #collaboration #learning #programming #source code: Learning to Write Programs with Others: Collaborative Quadruple Programming (RA, SG), pp. 32–41.
CSEET-2012-BareissS: A Gentle Introduction to Learn by Doing (RB, TS), pp. 81–84.
CSEET-2012-TillmannHXB #education #game studies #learning #named #social: Pex4Fun: Teaching and Learning Computer Science via Social Gaming (NT, JdH, TX, JB), pp. 90–91.
ITiCSE-2012-AsadB #aspect-oriented #concept #image #learning: Are children capable of learning image processing concepts?: cognitive and affective aspects (KA, MB), pp. 227–231.
ITiCSE-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.
ITiCSE-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.
ITiCSE-2012-CamaraPV #collaboration #evaluation #framework #learning #programming: Evaluation of a collaborative instructional framework for programming learning (LMSC, MPV, JÁVI), pp. 162–167.
ITiCSE-2012-ChristensenC #learning: Lectures abandoned: active learning by active seminars (HBC, AVC), pp. 16–21.
ITiCSE-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.
ITiCSE-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.
ITiCSE-2012-HamadaN #learning: A learning tool for MP3 audio compression (MH, HN), p. 397.
ITiCSE-2012-HiltonJ #array #education #learning #on the #testing: On teaching arrays with test-driven learning in WebIDE (MH, DSJ), pp. 93–98.
ITiCSE-2012-KrausePR #learning: Formal learning groups in an introductory CS course: a qualitative exploration (JK, IP, CR), pp. 315–320.
ITiCSE-2012-Larraza-MendiluzeGMMRALS: Nintendo® DS projects to learn computer input-output (ELM, NGV, JIM, JM, TRV, ISA, JFL, KS), p. 373.
ITiCSE-2012-Luxton-ReillyDPS #how #learning #process #student: Activities, affordances and attitude: how student-generated questions assist learning (ALR, PD, BP, RS), pp. 4–9.
ITiCSE-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.
ITiCSE-2012-MehtaKP #algorithm #learning #network: Forming project groups while learning about matching and network flows in algorithms (DPM, TMK, IP), pp. 40–45.
ITiCSE-2012-MeyerW #lessons learnt #programming: Programming studio: advances and lessons learned (CM, MW), p. 369.
ITiCSE-2012-MussaiL #animation #concept #learning #object-oriented: An animation as an illustrate tool for learning concepts in oop (YM, NL), p. 386.
ITiCSE-2012-MyllymakiH #case study #learning: Choosing a study mode in blended learning (MM, IH), pp. 291–296.
ITiCSE-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.
ITiCSE-2012-Sudol-DeLyserSC #comprehension #learning #problem: Code comprehension problems as learning events (LASD, MS, SC), pp. 81–86.
ITiCSE-2012-Velazquez-Iturbide #algorithm #approach #learning #refinement: Refinement of an experimental approach tocomputer-based, active learning of greedy algorithms (JÁVI), pp. 46–51.
FASE-2012-AlrajehKRU #learning #satisfiability #specification: Learning from Vacuously Satisfiable Scenario-Based Specifications (DA, JK, AR, SU), pp. 377–393.
TACAS-2012-DSilvaHKT #analysis #bound #learning: Numeric Bounds Analysis with Conflict-Driven Learning (VD, LH, DK, MT), pp. 48–63.
TACAS-2012-MertenHSCJ #automaton #learning: Demonstrating Learning of Register Automata (MM, FH, BS, SC, BJ), pp. 466–471.
ICPC-2012-Sajnani #approach #architecture #automation #machine learning: Automatic software architecture recovery: A machine learning approach (HS), pp. 265–268.
ICSM-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.
SAS-2012-GiannakopoulouRR #component #interface #learning: Symbolic Learning of Component Interfaces (DG, ZR, VR), pp. 248–264.
STOC-2012-DaskalakisDS #learning: Learning poisson binomial distributions (CD, ID, RAS), pp. 709–728.
DLT-2012-BoiretLN #learning: Learning Rational Functions (AB, AL, JN), pp. 273–283.
LATA-2012-GeilkeZ #algorithm #learning #pattern matching #polynomial: Polynomial-Time Algorithms for Learning Typed Pattern Languages (MG, SZ), pp. 277–288.
LATA-2012-Yoshinaka #context-free grammar #integration #learning: Integration of the Dual Approaches in the Distributional Learning of Context-Free Grammars (RY), pp. 538–550.
FM-2012-AartsHKOV #abstraction #automaton #learning #refinement: Automata Learning through Counterexample Guided Abstraction Refinement (FA, FH, HK, PO, FWV), pp. 10–27.
CHI-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.
CHI-2012-ChinF #difference #health #learning: Age differences in exploratory learning from a health information website (JC, WTF), pp. 3031–3040.
CHI-2012-DongDJKNA #game studies #learning: Discovery-based games for learning software (TD, MD, DJ, KK, MWN, MSA), pp. 2083–2086.
CHI-2012-JainB #learning #performance: User learning and performance with bezel menus (MJ, RB), pp. 2221–2230.
CHI-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.
CHI-2012-ParkC12a #adaptation #deployment #design #learning: Adaptation as design: learning from an EMR deployment study (SYP, YC), pp. 2097–2106.
CHI-2012-VitakIDEG #learning: Gaze-augmented think-aloud as an aid to learning (SAV, JEI, ATD, SE, AKG), pp. 2991–3000.
CHI-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.
CSCW-2012-HemphillO #adaptation #bibliography #community #gender #learning: Learning the lingo?: gender, prestige and linguistic adaptation in review communities (LH, JO), pp. 305–314.
CSCW-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.
CSCW-2012-RzeszotarskiK #learning #predict #wiki #word: Learning from history: predicting reverted work at the word level in wikipedia (JMR, AK), pp. 437–440.
CSCW-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.
ICEIS-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.
ICEIS-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.
CIKM-2012-AgarwalRSMLGF #learning #rank #robust: Learning to rank for robust question answering (AA, HR, KS, PM, RDL, DG, JF), pp. 833–842.
CIKM-2012-AnHS #learning #ontology #web: Learning to discover complex mappings from web forms to ontologies (YA, XH, IYS), pp. 1253–1262.
CIKM-2012-CaiZ #injection #learning #rank: Variance maximization via noise injection for active sampling in learning to rank (WC, YZ), pp. 1809–1813.
CIKM-2012-ChaliHI #learning #performance: Improving the performance of the reinforcement learning model for answering complex questions (YC, SAH, KI), pp. 2499–2502.
CIKM-2012-ChengZXAC #classification #learning #on the: On active learning in hierarchical classification (YC, KZ, YX, AA, ANC), pp. 2467–2470.
CIKM-2012-Cohen #learning #metric #random #similarity: Learning similarity measures based on random walks (WWC), p. 3.
CIKM-2012-CuiMWGL #image #keyword #semantics: Semantically coherent image annotation with a learning-based keyword propagation strategy (CC, JM, SW, SG, TL), pp. 2423–2426.
CIKM-2012-FangS #approach #feedback #learning #recommendation: A latent pairwise preference learning approach for recommendation from implicit feedback (YF, LS), pp. 2567–2570.
CIKM-2012-GuoMCJ #learning #recommendation #social: Learning to recommend with social relation ensemble (LG, JM, ZC, HJ), pp. 2599–2602.
CIKM-2012-KanhabuaN #learning #query #rank: Learning to rank search results for time-sensitive queries (NK, KN), pp. 2463–2466.
CIKM-2012-LiBCH #clustering #learning #relational: Relational co-clustering via manifold ensemble learning (PL, JB, CC, ZH), pp. 1687–1691.
CIKM-2012-LuZZX #image #learning #scalability #semantics #set: Semantic context learning with large-scale weakly-labeled image set (YL, WZ, KZ, XX), pp. 1859–1863.
CIKM-2012-MacdonaldSO #learning #on the #query #rank: On the usefulness of query features for learning to rank (CM, RLTS, IO), pp. 2559–2562.
CIKM-2012-MetzgerSHS #interactive #learning: LUKe and MIKe: learning from user knowledge and managing interactive knowledge extraction (SM, MS, KH, RS), pp. 2671–2673.
CIKM-2012-MorenoSRS #learning #multi #named: TALMUD: transfer learning for multiple domains (OM, BS, LR, GS), pp. 425–434.
CIKM-2012-NegahbanRG #learning #multi #performance #scalability #statistics #using: Scaling multiple-source entity resolution using statistically efficient transfer learning (SN, BIPR, JG), pp. 2224–2228.
CIKM-2012-QuanzH #generative #learning #multi #named: CoNet: feature generation for multi-view semi-supervised learning with partially observed views (BQ, JH), pp. 1273–1282.
CIKM-2012-RamanSGB #algorithm #learning #towards: Learning from mistakes: towards a correctable learning algorithm (KR, KMS, RGB, CJCB), pp. 1930–1934.
CIKM-2012-RenCJ #learning #topic: Topic based pose relevance learning in dance archives (RR, JPC, JMJ), pp. 2571–2574.
CIKM-2012-ShangJLW #learning: Learning spectral embedding via iterative eigenvalue thresholding (FS, LCJ, YL, FW), pp. 1507–1511.
CIKM-2012-SunG #learning: Active learning for relation type extension with local and global data views (AS, RG), pp. 1105–1112.
CIKM-2012-SunSL #learning #multi #performance #query: Fast multi-task learning for query spelling correction (XS, AS, PL), pp. 285–294.
CIKM-2012-SunWGM #hybrid #learning #rank #recommendation: Learning to rank for hybrid recommendation (JS, SW, BJG, JM), pp. 2239–2242.
CIKM-2012-VolkovsLZ #learning #rank: Learning to rank by aggregating expert preferences (MV, HL, RSZ), pp. 843–851.
CIKM-2012-WangC #learning #predict #word: Learning to predict the cost-per-click for your ad words (CJW, HHC), pp. 2291–2294.
CIKM-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.
CIKM-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.
CIKM-2012-WangXY #learning: Importance weighted passive learning (SW, XX, YY), pp. 2243–2246.
CIKM-2012-YangTKZLDLW #learning #mining #network: Mining competitive relationships by learning across heterogeneous networks (YY, JT, JK, YZ, JL, YD, TL, LW), pp. 1432–1441.
CIKM-2012-YaoS #learning #relational #ubiquitous: Exploiting latent relevance for relational learning of ubiquitous things (LY, QZS), pp. 1547–1551.
CIKM-2012-ZhangHLL #learning #rank #realtime #twitter: Query-biased learning to rank for real-time twitter search (XZ, BH, TL, BL), pp. 1915–1919.
CIKM-2012-ZhangWW #framework #interactive #learning #ontology: An interaction framework of service-oriented ontology learning (JZ, YW, HW), pp. 2303–2306.
CIKM-2012-ZhouLZ #community #learning #quality: Joint relevance and answer quality learning for question routing in community QA (GZ, KL, JZ), pp. 1492–1496.
CIKM-2012-ZhouZ #debugging #learning #rank: Learning to rank duplicate bug reports (JZ, HZ), pp. 852–861.
ECIR-2012-Lubell-DoughtieH #feedback #learning #rank: Learning to Rank from Relevance Feedback for e-Discovery (PLD, KH), pp. 535–539.
ECIR-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.
ICML-2012-AzarMK #complexity #generative #learning #on the: On the Sample Complexity of Reinforcement Learning with a Generative Model (MGA, RM, BK), p. 222.
ICML-2012-AzimiFFBH #coordination #learning: Batch Active Learning via Coordinated Matching (JA, AF, XZF, GB, BH), p. 44.
ICML-2012-BalleQC #learning #modelling #optimisation: Local Loss Optimization in Operator Models: A New Insight into Spectral Learning (BB, AQ, XC), p. 236.
ICML-2012-BelletHS #classification #learning #linear #similarity: Similarity Learning for Provably Accurate Sparse Linear Classification (AB, AH, MS), p. 193.
ICML-2012-BonillaR #learning #probability #prototype: Discriminative Probabilistic Prototype Learning (EVB, ARK), p. 155.
ICML-2012-BronsteinSS #learning #modelling #performance: Learning Efficient Structured Sparse Models (AMB, PS, GS), p. 33.
ICML-2012-ChambersJ #learning: Learning the Central Events and Participants in Unlabeled Text (NC, DJ), p. 3.
ICML-2012-CharlinZB #learning #problem: Active Learning for Matching Problems (LC, RSZ, CB), p. 23.
ICML-2012-DekelTA #adaptation #learning #online #policy: Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret (OD, AT, RA), p. 227.
ICML-2012-DuanXT #adaptation #learning: Learning with Augmented Features for Heterogeneous Domain Adaptation (LD, DX, IWT), p. 89.
ICML-2012-DundarAQR #learning #modelling #online: Bayesian Nonexhaustive Learning for Online Discovery and Modeling of Emerging Classes (MD, FA, AQ, BR), p. 18.
ICML-2012-EbanBSG #learning #online #predict #sequence: Learning the Experts for Online Sequence Prediction (EE, AB, SSS, AG), p. 38.
ICML-2012-FarabetCNL #learning #multi #parsing: Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers (CF, CC, LN, YL), p. 241.
ICML-2012-GeistSLG #approach #difference #learning: A Dantzig Selector Approach to Temporal Difference Learning (MG, BS, AL, MG), p. 49.
ICML-2012-Gonen #kernel #learning #multi #performance: Bayesian Efficient Multiple Kernel Learning (MG), p. 17.
ICML-2012-GongZM #learning #multi #robust: Robust Multiple Manifold Structure Learning (DG, XZ, GGM), p. 7.
ICML-2012-GoodfellowCB #learning #scalability: Large-Scale Feature Learning With Spike-and-Slab Sparse Coding (IJG, ACC, YB), p. 180.
ICML-2012-GuoX #classification #learning #multi: Cross Language Text Classification via Subspace Co-regularized Multi-view Learning (YG, MX), p. 120.
ICML-2012-HanLC #learning #modelling #multi: Cross-Domain Multitask Learning with Latent Probit Models (SH, XL, LC), p. 51.
ICML-2012-HazanK #learning #online: Projection-free Online Learning (EH, SK), p. 239.
ICML-2012-HoiWZ #learning: Exact Soft Confidence-Weighted Learning (SCHH, JW, PZ), p. 19.
ICML-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.
ICML-2012-Honorio #convergence #learning #modelling #optimisation #probability: Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising Models (JH), p. 144.
ICML-2012-JalaliS #dependence #graph #learning: Learning the Dependence Graph of Time Series with Latent Factors (AJ, SS), p. 83.
ICML-2012-JawanpuriaN #learning: A Convex Feature Learning Formulation for Latent Task Structure Discovery (PJ, JSN), p. 199.
ICML-2012-JiangLS #3d #learning #using: Learning Object Arrangements in 3D Scenes using Human Context (YJ, ML, AS), p. 119.
ICML-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.
ICML-2012-KalakrishnanRPS #learning #policy: Learning Force Control Policies for Compliant Robotic Manipulation (MK, LR, PP, SS), p. 10.
ICML-2012-KarbasiIM #learning #rank: Comparison-Based Learning with Rank Nets (AK, SI, LM), p. 161.
ICML-2012-KumarD #learning #multi: Learning Task Grouping and Overlap in Multi-task Learning (AK, HDI), p. 224.
ICML-2012-KumarNKD #classification #framework #kernel #learning #multi: A Binary Classification Framework for Two-Stage Multiple Kernel Learning (AK, ANM, KK, HDI), p. 173.
ICML-2012-KumarPK #learning #modelling #nondeterminism: Modeling Latent Variable Uncertainty for Loss-based Learning (MPK, BP, DK), p. 29.
ICML-2012-LanctotGBB #game studies #learning: No-Regret Learning in Extensive-Form Games with Imperfect Recall (ML, RGG, NB, MB), p. 135.
ICML-2012-LeRMDCCDN #learning #scalability #using: Building high-level features using large scale unsupervised learning (QVL, MR, RM, MD, GC, KC, JD, AYN), p. 69.
ICML-2012-LinXWZ #learning: Total Variation and Euler’s Elastica for Supervised Learning (TL, HX, LW, HZ), p. 82.
ICML-2012-LouH #learning: Structured Learning from Partial Annotations (XL, FAH), p. 52.
ICML-2012-MakinoT #learning #parametricity: Apprenticeship Learning for Model Parameters of Partially Observable Environments (TM, JT), p. 117.
ICML-2012-MatuszekFZBF #learning: A Joint Model of Language and Perception for Grounded Attribute Learning (CM, NF, LSZ, LB, DF), p. 186.
ICML-2012-Memisevic #learning #multi #on the: On multi-view feature learning (RM), p. 140.
ICML-2012-MnihH #image #learning #semistructured data: Learning to Label Aerial Images from Noisy Data (VM, GEH), p. 31.
ICML-2012-MohamedHG #learning: Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning (SM, KAH, ZG), p. 91.
ICML-2012-NiuDYS #learning #metric: Information-theoretic Semi-supervised Metric Learning via Entropy Regularization (GN, BD, MY, MS), p. 136.
ICML-2012-Painter-WakefieldP #algorithm #learning: Greedy Algorithms for Sparse Reinforcement Learning (CPW, RP), p. 114.
ICML-2012-PassosRWD #flexibility #learning #modelling #multi: Flexible Modeling of Latent Task Structures in Multitask Learning (AP, PR, JW, HDI), p. 167.
ICML-2012-PeharzP #learning #network: Exact Maximum Margin Structure Learning of Bayesian Networks (RP, FP), p. 102.
ICML-2012-PiresS #estimation #learning #linear #statistics: Statistical linear estimation with penalized estimators: an application to reinforcement learning (BAP, CS), p. 228.
ICML-2012-PlessisS #learning: Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching (MCdP, MS), p. 159.
ICML-2012-PrasseSLS #email #identification #learning #regular expression: Learning to Identify Regular Expressions that Describe Email Campaigns (PP, CS, NL, TS), p. 146.
ICML-2012-RossB #identification #learning #modelling: Agnostic System Identification for Model-Based Reinforcement Learning (SR, DB), p. 247.
ICML-2012-SamdaniR #learning #performance #predict: Efficient Decomposed Learning for Structured Prediction (RS, DR), p. 200.
ICML-2012-ScholkopfJPSZM #learning #on the: On causal and anticausal learning (BS, DJ, JP, ES, KZ, JMM), p. 63.
ICML-2012-ShiS #adaptation #clustering #learning: Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation (YS, FS), p. 166.
ICML-2012-ShivaswamyJ #learning #online #predict: Online Structured Prediction via Coactive Learning (PS, TJ), p. 12.
ICML-2012-SilvaKB #learning: Learning Parameterized Skills (BCdS, GK, AGB), p. 187.
ICML-2012-SohnL #invariant #learning: Learning Invariant Representations with Local Transformations (KS, HL), p. 174.
ICML-2012-StorkeyMG #machine learning: Isoelastic Agents and Wealth Updates in Machine Learning Markets (AJS, JM, KG), p. 133.
ICML-2012-Wagstaff #machine learning #matter: Machine Learning that Matters (KW), p. 240.
ICML-2012-WangWHL #learning #monte carlo: Monte Carlo Bayesian Reinforcement Learning (YW, KSW, DH, WSL), p. 105.
ICML-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.
ICML-2012-XuWC #learning: The Greedy Miser: Learning under Test-time Budgets (ZEX, KQW, OC), p. 169.
ICML-2012-YackleyL #learning: Smoothness and Structure Learning by Proxy (BY, TL), p. 57.
ICML-2012-YangMJZZ #kernel #learning #multi #probability #programming: Multiple Kernel Learning from Noisy Labels by Stochastic Programming (TY, MM, RJ, LZ, YZ), p. 21.
ICML-2012-ZhongK #clustering #flexibility #learning #multi: Convex Multitask Learning with Flexible Task Clusters (WZ, JTYK), p. 66.
ICPR-2012-AbeOD #image #learning #rank: Recognizing surface qualities from natural images based on learning to rank (TA, TO, KD), pp. 3712–3715.
ICPR-2012-AntoniukFH #learning #markov #network: Learning Markov Networks by Analytic Center Cutting Plane Method (KA, VF, VH), pp. 2250–2253.
ICPR-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.
ICPR-2012-BaillyMPB #cost analysis #learning: Learning global cost function for face alignment (KB, MM, PP, EB), pp. 1112–1115.
ICPR-2012-BanerjeeN #kernel #learning #multi #process #recognition #using: Pose based activity recognition using Multiple Kernel learning (PB, RN), pp. 445–448.
ICPR-2012-CermanH #learning #problem: Tracking with context as a semi-supervised learning and labeling problem (LC, VH), pp. 2124–2127.
ICPR-2012-ChernoffLN #fault #learning #metric: Metric learning by directly minimizing the k-NN training error (KC, ML, MN), pp. 1265–1268.
ICPR-2012-DahmaneLDB #estimation #learning #symmetry: Learning symmetrical model for head pose estimation (AD, SL, CD, IMB), pp. 3614–3617.
ICPR-2012-DAmbrosioIS #learning #re-engineering: A One-per-Class reconstruction rule for class imbalance learning (RD, GI, PS), pp. 1310–1313.
ICPR-2012-DoTT #multi #representation #using: Text/graphic separation using a sparse representation with multi-learned dictionaries (THD, ST, ORT), pp. 689–692.
ICPR-2012-DuanWLDC #learning #named: K-CPD: Learning of overcomplete dictionaries for tensor sparse coding (GD, HW, ZL, JD, YWC), pp. 493–496.
ICPR-2012-FangZ #learning: I don’t know the label: Active learning with blind knowledge (MF, XZ), pp. 2238–2241.
ICPR-2012-FiaschiKNH #learning: Learning to count with regression forest and structured labels (LF, UK, RN, FAH), pp. 2685–2688.
ICPR-2012-GhanemKFZ #automation #learning #recognition: Context-aware learning for automatic sports highlight recognition (BG, MK, MF, TZ), pp. 1977–1980.
ICPR-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.
ICPR-2012-GranaCBC #image #learning #segmentation: Learning non-target items for interesting clothes segmentation in fashion images (CG, SC, DB, RC), pp. 3317–3320.
ICPR-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.
ICPR-2012-GutmannH #architecture #feature model #image #learning: Learning a selectivity-invariance-selectivity feature extraction architecture for images (MG, AH), pp. 918–921.
ICPR-2012-HidoK #graph #learning #similarity: Hash-based structural similarity for semi-supervised Learning on attribute graphs (SH, HK), pp. 3009–3012.
ICPR-2012-HinoO #kernel #learning #multi: An improved entropy-based multiple kernel learning (HH, TO), pp. 1189–1192.
ICPR-2012-HiradeY #learning #predict: Ensemble learning for change-point prediction (RH, TY), pp. 1860–1863.
ICPR-2012-HuangLT #invariant #learning #recognition: Learning modality-invariant features for heterogeneous face recognition (LH, JL, YPT), pp. 1683–1686.
ICPR-2012-JinGYZ #algorithm #learning #multi: Multi-label learning vector quantization algorithm (XBJ, GG, JY, DZ), pp. 2140–2143.
ICPR-2012-JiS12a #3d #estimation #learning #robust: Robust 3D human pose estimation via dual dictionaries learning (HJ, FS), pp. 3370–3373.
ICPR-2012-KhanT #learning #taxonomy: Stable discriminative dictionary learning via discriminative deviation (NK, MFT), pp. 3224–3227.
ICPR-2012-KongW #clustering #learning #multi: A multi-task learning strategy for unsupervised clustering via explicitly separating the commonality (SK, DW), pp. 771–774.
ICPR-2012-KrijtheHL #classification #using: Improving cross-validation based classifier selection using meta-learning (JHK, TKH, ML), pp. 2873–2876.
ICPR-2012-KumarRS #learning #predict: Learning to predict super resolution wavelet coefficients (NK, NKR, AS), pp. 3468–3471.
ICPR-2012-KumarYD #classification #documentation #learning #retrieval: Learning document structure for retrieval and classification (JK, PY, DSD), pp. 1558–1561.
ICPR-2012-LeeKD #induction #learning: Learning action symbols for hierarchical grammar induction (KL, TKK, YD), pp. 3778–3782.
ICPR-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.
ICPR-2012-LiHL #adaptation #learning #multi #online #people: Online adaptive learning for multi-camera people counting (JL, LH, CL), pp. 3415–3418.
ICPR-2012-LiLLL #distance #estimation #learning #metric: Learning distance metric regression for facial age estimation (CL, QL, JL, HL), pp. 2327–2330.
ICPR-2012-LinLZ #learning #representation #taxonomy: Incoherent dictionary learning for sparse representation (TL, SL, HZ), pp. 1237–1240.
ICPR-2012-LiPMH #classification #email #incremental #learning #using: Business email classification using incremental subspace learning (ML, YP, RM, HYH), pp. 625–628.
ICPR-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.
ICPR-2012-LiuL #analysis #detection #learning #multi: Unsupervised multi-target trajectory detection, learning and analysis in complicated environments (HL, JL), pp. 3716–3720.
ICPR-2012-LiuLWZ #learning #linear: Locally linear embedding based example learning for pan-sharpening (QL, LL, YW, ZZ), pp. 1928–1931.
ICPR-2012-LiuLYZ #composition #learning #visual notation: Learning to describe color composition of visual objects (YL, YL, ZY, NZ), pp. 3337–3340.
ICPR-2012-LiuML #learning #multi: Training data recycling for multi-level learning (JL, SM, YL), pp. 2314–2318.
ICPR-2012-LiuSW #learning #recognition #taxonomy: Facial expression recognition based on discriminative dictionary learning (WL, CS, YW), pp. 1839–1842.
ICPR-2012-LiVBB #clustering #learning #using: Feature learning using Generalized Extreme Value distribution based K-means clustering (ZL, OV, HB, RB), pp. 1538–1541.
ICPR-2012-LuLY #adaptation #classification #kernel #learning: Adaptive kernel learning based on centered alignment for hierarchical classification (YL, JL, JY), pp. 569–572.
ICPR-2012-LuLZSCO #using: Learning-based deformable registration using weighted mutual information (YL, RL, LZ, YS, CC, SHO), pp. 2626–2629.
ICPR-2012-MarcaciniCR #approach #clustering #learning: An active learning approach to frequent itemset-based text clustering (RMM, GNC, SOR), pp. 3529–3532.
ICPR-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.
ICPR-2012-MoZW #classification #learning: Enhancing cross-view object classification by feature-based transfer learning (YM, ZZ, YW), pp. 2218–2221.
ICPR-2012-Nagy #learning #web: Learning the characteristics of critical cells from web tables (GN), pp. 1554–1557.
ICPR-2012-NamA #image #learning: Learning human preferences to sharpen images (MN, NA), pp. 2173–2176.
ICPR-2012-NayefAB #learning: Learning feature weights of symbols, with application to symbol spotting (NN, MZA, TMB), pp. 2371–2374.
ICPR-2012-Noh #analysis #classification #learning #metric #nearest neighbour: χ2 Metric learning for nearest neighbor classification and its analysis (SN), pp. 991–995.
ICPR-2012-PangHYQW #analysis #classification #learning: Theoretical analysis of learning local anchors for classification (JP, QH, BY, LQ, DW), pp. 1803–1806.
ICPR-2012-PanLS #kernel #learning: Learning kernels from labels with ideal regularization (BP, JHL, LS), pp. 505–508.
ICPR-2012-PourdamghaniRZ #estimation #graph #learning #metric: Metric learning for graph based semi-supervised human pose estimation (NP, HRR, MZ), pp. 3386–3389.
ICPR-2012-QinZCW #learning #online: Matting-driven online learning of Hough forests for object tracking (TQ, BZ, TJC, HW), pp. 2488–2491.
ICPR-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.
ICPR-2012-SchauerteS #image #learning #modelling #robust #web: Learning robust color name models from web images (BS, RS), pp. 3598–3601.
ICPR-2012-SharmaHN #classification #detection #incremental #learning #performance: Efficient incremental learning of boosted classifiers for object detection (PS, CH, RN), pp. 3248–3251.
ICPR-2012-ShenMZ #analysis #graph #learning #online: Unsupervised online learning trajectory analysis based on weighted directed graph (YS, ZM, JZ), pp. 1306–1309.
ICPR-2012-SommerFHG #detection #image: Learning-based mitotic cell detection in histopathological images (CS, LF, FAH, DG), pp. 2306–2309.
ICPR-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.
ICPR-2012-SunBM #learning: Unsupervised skeleton learning for manifold denoising (KS, EB, SMM), pp. 2719–2722.
ICPR-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.
ICPR-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.
ICPR-2012-TiribuziPVR #detection #framework #kernel #learning #multi: A Multiple Kernel Learning framework for detecting altered fingerprints (MT, MP, PV, ER), pp. 3402–3405.
ICPR-2012-TuS #adaptation #classification #learning: Dynamical ensemble learning with model-friendly classifiers for domain adaptation (WT, SS), pp. 1181–1184.
ICPR-2012-VillamizarGSM #learning #online #random #using: Online human-assisted learning using Random Ferns (MV, AG, AS, FMN), pp. 2821–2824.
ICPR-2012-VuralA #machine learning #video: A machine learning system for human-in-the-loop video surveillance (UV, YSA), pp. 1092–1095.
ICPR-2012-WangJ12b #learning #network #process #recognition: Learning dynamic Bayesian network discriminatively for human activity recognition (XW, QJ), pp. 3553–3556.
ICPR-2012-WangL12b #learning #recognition #string: String-level learning of confidence transformation for Chinese handwritten text recognition (DHW, CLL), pp. 3208–3211.
ICPR-2012-WeberBLS #learning #segmentation: Unsupervised motion pattern learning for motion segmentation (MW, GB, ML, DS), pp. 202–205.
ICPR-2012-XiaTWLL #categorisation #learning: Object categorization based on hierarchical learning (TX, YYT, YW, HL, LL), pp. 1419–1422.
ICPR-2012-YangLZC #image #learning #multi #retrieval: Multi-view learning with batch mode active selection for image retrieval (WY, GL, LZ, EC), pp. 979–982.
ICPR-2012-YanKMW #automation #game studies #learning: Automatic annotation of court games with structured output learning (FY, JK, KM, DW), pp. 3577–3580.
ICPR-2012-YanRLS #classification #learning #multi: Active transfer learning for multi-view head-pose classification (YY, SR, OL, NS), pp. 1168–1171.
ICPR-2012-YeD #learning #predict: Learning features for predicting OCR accuracy (PY, DSD), pp. 3204–3207.
ICPR-2012-ZhangHR #classification #gender #learning: Hypergraph based semi-supervised learning for gender classification (ZZ, ERH, PR), pp. 1747–1750.
ICPR-2012-ZhangZNH #learning #multi #recognition: Joint dynamic sparse learning and its application to multi-view face recognition (HZ, YZ, NMN, TSH), pp. 1671–1674.
ICPR-2012-ZhaoSS #learning #predict: Importance-weighted label prediction for active learning with noisy annotations (LZ, GS, RS), pp. 3476–3479.
ICPR-2012-ZhaoXY #learning #network #speech: Unsupervised Tibetan speech features Learning based on Dynamic Bayesian Networks (YZ, XX, GY), pp. 2319–2322.
ICPR-2012-ZhaoYXJ #learning: A near-optimal non-myopic active learning method (YZ, GY, XX, QJ), pp. 1715–1718.
ICPR-2012-ZhouWXZM #learning #recognition: Learning weighted features for human action recognition (WZ, CW, BX, ZZ, LM), pp. 1160–1163.
ICPR-2012-ZhuoCQYX #algorithm #classification #image #learning #using: Image classification using HTM cortical learning algorithms (WZ, ZC, YQ, ZY, YX), pp. 2452–2455.
KDD-2012-GongYZ #learning #multi #robust: Robust multi-task feature learning (PG, JY, CZ), pp. 895–903.
KDD-2012-HalawiDGK #constraints #learning #scalability #word: Large-scale learning of word relatedness with constraints (GH, GD, EG, YK), pp. 1406–1414.
KDD-2012-HoensC #learning: Learning in non-stationary environments with class imbalance (TRH, NVC), pp. 168–176.
KDD-2012-JainVV #kernel #learning #multi #named: SPF-GMKL: generalized multiple kernel learning with a million kernels (AJ, SVNV, MV), pp. 750–758.
KDD-2012-LiJPS #classification #learning #multi: Multi-domain active learning for text classification (LL, XJ, SJP, JTS), pp. 1086–1094.
KDD-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.
KDD-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.
KDD-2012-Posse #lessons learnt #network #recommendation #scalability #social: Key lessons learned building recommender systems for large-scale social networks (CP), p. 587.
KDD-2012-RamanSJ #feedback #learning #online: Online learning to diversify from implicit feedback (KR, PS, TJ), pp. 705–713.
KDD-2012-SeelandKK #clustering #graph #kernel #learning: A structural cluster kernel for learning on graphs (MS, AK, SK), pp. 516–524.
KDD-2012-ShangJW #learning: Semi-supervised learning with mixed knowledge information (FS, LCJ, FW), pp. 732–740.
KDD-2012-ShenJ #learning #recommendation #social: Learning personal + social latent factor model for social recommendation (YS, RJ), pp. 1303–1311.
KDD-2012-SilvaC #learning #matrix #online: Active learning for online bayesian matrix factorization (JGS, LC), pp. 325–333.
KDD-2012-SindhwaniG #distributed #learning #scalability #taxonomy: Large-scale distributed non-negative sparse coding and sparse dictionary learning (VS, AG), pp. 489–497.
KDD-2012-TianZ #learning: Learning from crowds in the presence of schools of thought (YT, JZ), pp. 226–234.
KDD-2012-XiongJXC #dependence #learning #metric #random: Random forests for metric learning with implicit pairwise position dependence (CX, DMJ, RX, JJC), pp. 958–966.
KDD-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.
KDD-2012-ZhangH #induction #learning #multi: Inductive multi-task learning with multiple view data (JZ, JH), pp. 543–551.
KDD-2012-ZhenY #learning #multimodal #probability: A probabilistic model for multimodal hash function learning (YZ, DYY), pp. 940–948.
KDD-2012-ZhouKTX #machine learning: Adversarial support vector machine learning (YZ, MK, BMT, BX), pp. 1059–1067.
KDD-2012-ZhouZ #collaboration #learning: Learning binary codes for collaborative filtering (KZ, HZ), pp. 498–506.
KDIR-2012-AbdullinN #clustering #data type #framework #learning: A Semi-supervised Learning Framework to Cluster Mixed Data Types (AA, ON), pp. 45–54.
KDIR-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.
KDIR-2012-Dagnino #approach #grid #information management #machine learning #smarttech: Knowledge Discovery in the Smart Grid — A Machine Learning Approach (AD), pp. 366–369.
KDIR-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.
KDIR-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.
KEOD-2012-GarciaAGG #case study #metadata #ontology: Case Study: Ontology for Metadata in e-Learning (AMFG, SSA, MEBG, RBG), pp. 317–320.
KEOD-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.
KEOD-2012-WohlgenanntWSS #learning #ontology #web: Confidence Management for Learning Ontologies from Dynamic Web Sources (GW, AW, AS, MS), pp. 172–177.
KMIS-2012-AkiyoshiSK #learning #problem #towards: A Project Manager Skill-up Simulator Towards Problem Solving-based Learning (MA, MS, NK), pp. 190–195.
KMIS-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.
KMIS-2012-HackerMHHM #collaboration #learning: Management of Collaboration — Impacts of Virtualization to Learning & Knowledge (GH, MM, PH, GH, MM), pp. 235–239.
KMIS-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.
KMIS-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.
KR-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).
MLDM-2012-BouhamedMLR #heuristic #learning #network: A New Learning Structure Heuristic of Bayesian Networks from Data (HB, AM, TL, AR), pp. 183–197.
MLDM-2012-ChanguelL #independence #machine learning #metadata #problem: Content Independent Metadata Production as a Machine Learning Problem (SC, NL), pp. 306–320.
MLDM-2012-HoaD #learning: A New Learning Strategy of General BAMs (NTH, TDB), pp. 213–221.
MLDM-2012-PitelisT #learning: Discriminant Subspace Learning Based on Support Vectors Machines (NP, AT), pp. 198–212.
MLDM-2012-TabatabaeiAKK #classification #internet #machine learning: Machine Learning-Based Classification of Encrypted Internet Traffic (TST, MA, FK, MK), pp. 578–592.
MLDM-2012-ToussaintB #comparison #empirical #learning: Proximity-Graph Instance-Based Learning, Support Vector Machines, and High Dimensionality: An Empirical Comparison (GTT, CB), pp. 222–236.
MLDM-2012-XuCG #concept #learning #multi #using: Constructing Target Concept in Multiple Instance Learning Using Maximum Partial Entropy (TX, DKYC, IG), pp. 169–182.
RecSys-2012-DeDGM #difference #learning #using: Local learning of item dissimilarity using content and link structure (AD, MSD, NG, PM), pp. 221–224.
RecSys-2012-Herbrich #distributed #learning #online #realtime: Distributed, real-time bayesian learning in online services (RH), pp. 203–204.
RecSys-2012-KarimiFNS #learning #matrix #recommendation: Exploiting the characteristics of matrix factorization for active learning in recommender systems (RK, CF, AN, LST), pp. 317–320.
RecSys-2012-Kohavi #online #statistics: Online controlled experiments: introduction, learnings, and humbling statistics (RK), pp. 1–2.
RecSys-2012-SalimansPG #collaboration #learning #ranking: Collaborative learning of preference rankings (TS, UP, TG), pp. 261–264.
RecSys-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.
SEKE-2012-AlawawdehAL #adaptation #collaboration #learning #named: CLAT: Collaborative Learning Adaptive Tutor (AMHA, CA, LL), pp. 747–752.
SEKE-2012-DagninoSR #fault #machine learning #using: Forecasting Fault Events in Power Distribution Grids Using Machine Learning (AD, KS, LR), pp. 458–463.
SEKE-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.
SEKE-2012-HaoWZ #classification #empirical #machine learning: An Empirical Study of Execution-Data Classification Based on Machine Learning (DH, XW, LZ), pp. 283–288.
SEKE-2012-XavierOC #fuzzy #learning #logic: Evolutionary Learning and Fuzzy Logic Applied to a Load Balancer (FCX, MGdO, CLdC), pp. 256–260.
SEKE-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.
SEKE-2012-Zhang #bias #learning #named: i2Learning: Perpetual Learning through Bias Shifting (DZ), pp. 249–255.
SIGIR-2012-BilgicB #learning #query: Active query selection for learning rankers (MB, PNB), pp. 1033–1034.
SIGIR-2012-ChangHYLC #ranking #web: Learning-based time-sensitive re-ranking for web search (PTC, YCH, CLY, SDL, PJC), pp. 1101–1102.
SIGIR-2012-GaoWL #graph #information retrieval #learning #mining #scalability: Large-scale graph mining and learning for information retrieval (BG, TW, TYL), pp. 1194–1195.
SIGIR-2012-HongBAD #learning #rank #social: Learning to rank social update streams (LH, RB, JA, BDD), pp. 651–660.
SIGIR-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.
SIGIR-2012-KanhabuaBN #learning #retrieval: Learning to select a time-aware retrieval model (NK, KB, KN), pp. 1099–1100.
SIGIR-2012-KovesiGA #categorisation #learning #multi #online #performance: Fast on-line learning for multilingual categorization (MK, CG, MRA), pp. 1071–1072.
SIGIR-2012-LiX #machine learning #web: Beyond bag-of-words: machine learning for query-document matching in web search (HL, JX), p. 1177.
SIGIR-2012-MacdonaldTO #learning #online #predict #query #scheduling: Learning to predict response times for online query scheduling (CM, NT, IO), pp. 621–630.
SIGIR-2012-MacdonaldTO12a #effectiveness #learning #rank #safety: Effect of dynamic pruning safety on learning to rank effectiveness (CM, NT, IO), pp. 1051–1052.
SIGIR-2012-NiuGLC #evaluation #learning #rank #ranking: Top-k learning to rank: labeling, ranking and evaluation (SN, JG, YL, XC), pp. 751–760.
SIGIR-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.
SIGIR-2012-SeverynM #learning #ranking #scalability: Structural relationships for large-scale learning of answer re-ranking (AS, AM), pp. 741–750.
SIGIR-2012-ZhangWDH #detection #learning #performance #reuse: Learning hash codes for efficient content reuse detection (QZ, YW, ZD, XH), pp. 405–414.
OOPSLA-2012-KulkarniC #compilation #machine learning #optimisation #problem #using: Mitigating the compiler optimization phase-ordering problem using machine learning (SK, JC), pp. 147–162.
OOPSLA-2012-St-AmourTF #communication #optimisation: Optimization coaching: optimizers learn to communicate with programmers (VSA, STH, MF), pp. 163–178.
TOOLS-EUROPE-2012-Sureka #component #debugging #learning: Learning to Classify Bug Reports into Components (AS), pp. 288–303.
PADL-2012-ZhuFW #ad hoc #incremental: LearnPADS + + : Incremental Inference of Ad Hoc Data Formats (KQZ, KF, DW), pp. 168–182.
REFSQ-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.
REFSQ-2012-KnaussS #documentation #heuristic #learning #requirements: Supporting Learning Organisations in Writing Better Requirements Documents Based on Heuristic Critiques (EK, KS), pp. 165–171.
SAC-2012-MinervinidF #concept #learning #logic #probability: Learning probabilistic Description logic concepts: under different Assumptions on missing knowledge (PM, Cd, NF), pp. 378–383.
SAC-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.
SAC-2012-OongI #classification #fuzzy #learning #multi #performance #testing: Multilayer Fuzzy ARTMAP: fast learning and fast testing for pattern classification (THO, NAMI), pp. 27–32.
ICSE-2012-Chioasca #automation #machine learning #model transformation #requirements #using: Using machine learning to enhance automated requirements model transformation (EVC), pp. 1487–1490.
ICSE-2012-DagenaisR #api #learning #traceability: Recovering traceability links between an API and its learning resources (BD, MPR), pp. 47–57.
ICSE-2012-FengC #behaviour #learning #multi: Multi-label software behavior learning (YF, ZC), pp. 1305–1308.
ICSE-2012-GrechanikFX #automation #learning #performance #problem #testing: Automatically finding performance problems with feedback-directed learning software testing (MG, CF, QX), pp. 156–166.
ICSE-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.
CAV-2012-ChenW #incremental #learning: Learning Boolean Functions Incrementally (YFC, BYW), pp. 55–70.
CAV-2012-LeeWY #algorithm #analysis #learning #termination: Termination Analysis with Algorithmic Learning (WL, BYW, KY), pp. 88–104.
CAV-2012-SinhaSCS: Alternate and Learn: Finding Witnesses without Looking All over (NS, NS, SC, MS), pp. 599–615.
CSL-2012-Berardid #learning: Knowledge Spaces and the Completeness of Learning Strategies (SB, Ud), pp. 77–91.
ICLP-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.
ICLP-2012-MarateaPR #machine learning: Applying Machine Learning Techniques to ASP Solving (MM, LP, FR), pp. 37–48.
ICST-2012-RamlerKP #combinator #design #lessons learnt: Combinatorial Test Design in the TOSCA Testsuite: Lessons Learned and Practical Implications (RR, TK, WP), pp. 569–572.
ICST-2012-SunSPR #cost analysis #learning #named #reliability: CARIAL: Cost-Aware Software Reliability Improvement with Active Learning (BS, GS, AP, SR), pp. 360–369.
ICTSS-2012-StrugS #approach #machine learning #mutation testing #testing: Machine Learning Approach in Mutation Testing (JS, BS), pp. 200–214.
ICTSS-2012-Vaandrager #finite #learning #state machine: Active Learning of Extended Finite State Machines (FWV), pp. 5–7.
LICS-2012-KomuravelliPC #learning #probability: Learning Probabilistic Systems from Tree Samples (AK, CSP, EMC), pp. 441–450.
SAT-2012-BonetB #learning: An Improved Separation of Regular Resolution from Pool Resolution and Clause Learning (MLB, SRB), pp. 44–57.
SAT-2012-KatsirelosS #learning #satisfiability: Learning Polynomials over GF(2) in a SAT Solver — (Poster Presentation) (GK, LS), pp. 496–497.
SAT-2012-LaitinenJN #learning: Conflict-Driven XOR-Clause Learning (TL, TAJ, IN), pp. 383–396.
SAT-2012-MatsliahSS #learning: Augmenting Clause Learning with Implied Literals — (Poster Presentation) (AM, AS, HS), pp. 500–501.
SAT-2012-SabharwalSS #learning #satisfiability: Learning Back-Clauses in SAT — (Poster Presentation) (AS, HS, MS), pp. 498–499.
SMT-2012-AzizWD #estimation #machine learning #problem #smt: A Machine Learning Technique for Hardness Estimation of QFBV SMT Problems (MAA, AGW, NMD), pp. 57–66.
CBSE-2011-AletiM #component #deployment #learning #optimisation: Component deployment optimisation with bayesian learning (AA, IM), pp. 11–20.
ECSA-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.
ASE-2011-ChenHX #approach #evaluation #machine learning #process: Software process evaluation: A machine learning approach (NC, SCHH, XX), pp. 333–342.
DAC-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.
DAC-2011-GeQ #machine learning #multi #using: Dynamic thermal management for multimedia applications using machine learning (YG, QQ), pp. 95–100.
DAC-2011-KatzRZS #architecture #behaviour #generative #learning #quality: Learning microarchitectural behaviors to improve stimuli generation quality (YK, MR, AZ, GS), pp. 848–853.
DAC-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.
DATE-2011-ArslanO #adaptation #effectiveness #learning #optimisation #realtime: Adaptive test optimization through real time learning of test effectiveness (BA, AO), pp. 1430–1435.
DocEng-2011-ChidlovskiiB #learning #metric #network #recommendation #social: Local metric learning for tag recommendation in social networks (BC, AB), pp. 205–208.
ICDAR-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.
ICDAR-2011-KumarPD #classification #documentation #image #learning #multi #using: Document Image Classification and Labeling Using Multiple Instance Learning (JK, JP, DSD), pp. 1059–1063.
ICDAR-2011-ShaoWXZZ11a #learning #multi: Multiple Instance Learning Based Method for Similar Handwritten Chinese Characters Discrimination (YS, CW, BX, RZ, YZ), pp. 1002–1006.
ICDAR-2011-SuLZ #learning #polynomial: Perceptron Learning of Modified Quadratic Discriminant Function (THS, CLL, XYZ), pp. 1007–1011.
ICDAR-2011-TaoLJG #learning #locality #recognition #using: Similar Handwritten Chinese Character Recognition Using Discriminative Locality Alignment Manifold Learning (DT, LL, LJ, YG), pp. 1012–1016.
ICDAR-2011-VajdaJF #approach #learning: A Semi-supervised Ensemble Learning Approach for Character Labeling with Minimal Human Effort (SV, AJ, GAF), pp. 259–263.
ICDAR-2011-WangDL #learning #recognition: MQDF Discriminative Learning Based Offline Handwritten Chinese Character Recognition (YW, XD, CL), pp. 1100–1104.
SIGMOD-2011-GetoorM #learning #modelling #relational #statistics: Learning statistical models from relational data (LG, LM), pp. 1195–1198.
CSEET-2011-AndrianoMBR #assessment: A quantitative assessment method for simulation-based e-learnings (NA, MGM, CB, DR), pp. 159–168.
CSEET-2011-ChimalakondaN #education #learning #question #re-engineering: Can we make software engineering education better by applying learning theories? (SC, KVN), p. 561.
CSEET-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.
CSEET-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.
CSEET-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.
CSEET-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.
CSEET-2011-HattoriBLL #game studies #learning: Erase and rewind — Learning by replaying examples (LH, AB, ML, ML), p. 558.
CSEET-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.
CSEET-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.
CSEET-2011-TillmannHX #education #game studies #learning #named #social: Pex4Fun: Teaching and learning computer science via social gaming (NT, JdH, TX), pp. 546–548.
CSEET-2011-TuTOBHKY #learning: Turning real-world systems into verification-driven learning cases (ST, ST, SO, BB, BH, AK, ZY), pp. 129–138.
CSEET-2011-Virseda #education #learning #re-engineering #semantics: A learning methodology based on semantic tableaux for software engineering education (RdVV), pp. 401–405.
CSEET-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.
ITiCSE-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.
ITiCSE-2011-BowerM #comparison #learning: Continual and explicit comparison to promote proactive facilitation during second computer language learning (MB, AM), pp. 218–222.
ITiCSE-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.
ITiCSE-2011-CamachoM #learning #programming: Facilitating learning dynamic programming through a previous introduction of exhaustive search (AC, AM), p. 355.
ITiCSE-2011-ChanK: Do educational software systems provide satisfactory learning opportunities for “multi-sensory learning” methodology? (PC, GK), p. 358.
ITiCSE-2011-ChuaB #framework: Integrating scholarly articles within e-learning courses: a framework (BBC, DVB), p. 392.
ITiCSE-2011-EllisH #learning #named #student: Courseware: student learning via FOSS field trips (HJCE, GWH), p. 329.
ITiCSE-2011-GarciaMGH #interface #learning #unification: A system for usable unification of interfaces of learning objects in m-learning (EG, LdM, AGC, JRH), p. 347.
ITiCSE-2011-Goldweber #learning #process #turing machine: Two kinesthetic learning activities: turing machines and basic computer organization (MG), p. 335.
ITiCSE-2011-Goldweber11a #learning #social: Computing for the social good: a service learning project (MG), p. 379.
ITiCSE-2011-HarrachA #collaboration #learning #optimisation #process #recommendation #using: Optimizing collaborative learning processes by using recommendation systems (SH, MA), p. 389.
ITiCSE-2011-Hijon-NeiraV11a #design #learning: A first step mapping IMS learning design and Merlin-Mo (RHN, JÁVI), p. 365.
ITiCSE-2011-HoverHR #collaboration #learning: A collaborative linked learning space (KMH, MH, GR), p. 380.
ITiCSE-2011-HoverHRM #collaboration #how #learning #student: Evaluating how students would use a collaborative linked learning space (KMH, MH, GR, MM), pp. 88–92.
ITiCSE-2011-JourjonKY #framework: Impact of an e-learning platform on CSE lectures (GJ, SSK, JY), pp. 83–87.
ITiCSE-2011-KonertRGSB #ad hoc #community #learning: Supporting peer learning with ad-hoc communities (JK, KR, SG, RS, RB), p. 393.
ITiCSE-2011-LasserreS #learning: Effects of team-based learning on a CS1 course (PL, CS), pp. 133–137.
ITiCSE-2011-LuLJZJ #student: A bioinformatics e-learning lab for undergraduate students (FL, HL, YJ, YZ, ZJ), p. 356.
ITiCSE-2011-MartinezC #algebra #education #relational: A cooperative learning-based strategy for teaching relational algebra (AM, AC), pp. 263–267.
ITiCSE-2011-MesserK #problem #process: The use of mediating artifacts in embedding problem solving processes in an e-learning environment (OMM, AK), p. 390.
ITiCSE-2011-MothVB #learning #named #syntax: SyntaxTrain: relieving the pain of learning syntax (ALAM, JV, MBA), p. 387.
ITiCSE-2011-OliveiraMR #learning #problem #programming: From concrete to abstract?: problem domain in the learning of introductory programming (OLO, AMM, NTR), pp. 173–177.
ITiCSE-2011-PollockH #learning #multi: Combining multiple pedagogies to boost learning and enthusiasm (LLP, TH), pp. 258–262.
ITiCSE-2011-RussellMD #approach #learning #student: A contextualized project-based approach for improving student engagement and learning in AI courses (IR, ZM, JD), p. 368.
ITiCSE-2011-Sanchez-TorrubiaTT #algorithm #assessment #automation #learning: GLMP for automatic assessment of DFS algorithm learning (MGST, CTB, GT), p. 351.
ITiCSE-2011-ShuhidanHD #comprehension #learning: Understanding novice programmer difficulties via guided learning (SMS, MH, DJD), pp. 213–217.
ITiCSE-2011-VanoM #learning #quote: “Computer science and nursery rhymes”: a learning path for the middle school (DDV, CM), pp. 238–242.
ITiCSE-2011-WolzMS #learning #process: Kinesthetic learning of computing via “off-beat” activities (UW, MM, MS), pp. 68–72.
ESOP-2011-BorgstromGGMG #machine learning #semantics: Measure Transformer Semantics for Bayesian Machine Learning (JB, ADG, MG, JM, JVG), pp. 77–96.
FASE-2011-FengKP #automation #composition #learning #probability #reasoning: Automated Learning of Probabilistic Assumptions for Compositional Reasoning (LF, MZK, DP), pp. 2–17.
TACAS-2011-JungLWY #generative #invariant #quantifier: Predicate Generation for Learning-Based Quantifier-Free Loop Invariant Inference (YJ, WL, BYW, KY), pp. 205–219.
TACAS-2011-MertenSHM #generative: Next Generation LearnLib (MM, BS, FH, TMS), pp. 220–223.
ICPC-J-2009-Sanz-RodriguezDA11 #evaluation #learning #reuse: Metrics-based evaluation of learning object reusability (JSR, JMD, SSA), pp. 121–140.
CSMR-2011-Borchers #assessment #re-engineering: Invited Talk: Reengineering from a Practitioner’s View — A Personal Lesson’s Learned Assessment (JB), pp. 1–2.
SAS-2011-NoriR #machine learning #program analysis: Program Analysis and Machine Learning: A Win-Win Deal (AVN, SKR), pp. 2–3.
STOC-2011-BalcanH #learning: Learning submodular functions (MFB, NJAH), pp. 793–802.
DLT-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.
ICALP-v1-2011-AroraG #algorithm #fault #learning: New Algorithms for Learning in Presence of Errors (SA, RG), pp. 403–415.
ICALP-v1-2011-HarkinsH #algorithm #bound #game studies #learning: Exact Learning Algorithms, Betting Games, and Circuit Lower Bounds (RCH, JMH), pp. 416–423.
LATA-2011-CaseJLOSS #automation #learning #pattern matching #subclass: Automatic Learning of Subclasses of Pattern Languages (JC, SJ, TDL, YSO, PS, FS), pp. 192–203.
SFM-2011-Jonsson #automaton #learning #modelling: Learning of Automata Models Extended with Data (BJ), pp. 327–349.
SFM-2011-Moschitti #automation #kernel #learning #modelling: Kernel-Based Machines for Abstract and Easy Modeling of Automatic Learning (AM), pp. 458–503.
SFM-2011-SteffenHM #automaton #learning #perspective: Introduction to Active Automata Learning from a Practical Perspective (BS, FH, MM), pp. 256–296.
CHI-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.
CHI-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.
CHI-2011-EdgeSCZL #learning #mobile #named: MicroMandarin: mobile language learning in context (DE, ES, KC, JZ, JAL), pp. 3169–3178.
CHI-2011-FiebrinkCT #evaluation #interactive #learning: Human model evaluation in interactive supervised learning (RF, PRC, DT), pp. 147–156.
CHI-2011-HowisonTRA #concept #interactive #learning: The mathematical imagery trainer: from embodied interaction to conceptual learning (MH, DT, DR, DA), pp. 1989–1998.
CHI-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.
CHI-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.
CHI-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.
CHI-2011-ShaerSVFLW #interactive #learning: Enhancing genomic learning through tabletop interaction (OS, MS, CV, TF, ML, HW), pp. 2817–2826.
CHI-2011-ToupsKHS #coordination #learning #simulation: Zero-fidelity simulation of fire emergency response: improving team coordination learning (ZOT, AK, WAH, NS), pp. 1959–1968.
CHI-2011-TrustyT #learning #web: Augmenting the web for second language vocabulary learning (AT, KNT), pp. 3179–3188.
CSCW-2011-NawahdahI #automation #education #learning: Automatic adjustment of a virtual teacher’s model in a learning support system (MN, TI), pp. 693–696.
DHM-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.
DHM-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.
DUXU-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.
DUXU-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.
DUXU-v1-2011-GeorgeADMW #collaboration #learning #multi: Multitouch Tables for Collaborative Object-Based Learning (JG, EdA, DD, DSM, GW), pp. 237–246.
DUXU-v1-2011-Innes #design #enterprise #why: Why Enterprises Can’t Innovate: Helping Companies Learn Design Thinking (JI), pp. 442–448.
DUXU-v1-2011-LeeR #architecture #collaboration #concept #learning #mobile: Suggested Collaborative Learning Conceptual Architecture and Applications for Mobile Devices (KL, AR), pp. 611–620.
DUXU-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.
DUXU-v2-2011-ArditoLRSYAC #design #game studies #learning #pervasive: Designing Pervasive Games for Learning (CA, RL, DR, CS, NY, NMA, MFC), pp. 99–108.
HCD-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.
HCD-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.
HCI-MIIE-2011-KarthikP #adaptation #approach #classification #email #machine learning: Adaptive Machine Learning Approach for Emotional Email Classification (KK, RP), pp. 552–558.
HCI-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.
HCI-UA-2011-AdamsS #learning: A Web-Based Learning Environment to Support Chemistry (CA, CS), pp. 3–11.
HCI-UA-2011-EverardJM #learning #question #student #what: Are MIS Students Learning What They Need to Land a Job? (AE, BMJ, SM), pp. 235–236.
HCI-UA-2011-GeorgeS #collaboration #game studies #learning: Introducing Mobility in Serious Games: Enhancing Situated and Collaborative Learning (SG, AS), pp. 12–20.
HCI-UA-2011-HayakawaNOFN #framework #learning #visualisation: Visualization Framework for Computer System Learning (EH, YN, HO, MF, YN), pp. 21–26.
HCI-UA-2011-Huseyinov #adaptation #fuzzy #learning #modelling #multi: Fuzzy Linguistic Modelling Cognitive / Learning Styles for Adaptation through Multi-level Granulation (IH), pp. 39–47.
HCI-UA-2011-Klenner-Moore #learning #process: Creating a New Context for Activity in Blended Learning Environments: Engaging the Twitchy Fingers (JKM), pp. 61–67.
HCI-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.
HCI-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.
HCI-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.
HCI-UA-2011-YajimaT #collaboration #learning: Proposal of Collaborative Learning Support Method in Risk Communications (HY, NT), pp. 113–120.
HCI-UA-2011-YamaguchiMT #evaluation #learning #online: Evaluation of Online Handwritten Characters for Penmanship Learning Support System (TY, NM, MT), pp. 121–130.
HCI-UA-2011-YangCS #analysis #learning #recognition: Facial Expression Recognition for Learning Status Analysis (MTY, YJC, YCS), pp. 131–138.
HIMI-v2-2011-PohlML #hybrid #learning #standard: Transforming a Standard Lecture into a Hybrid Learning Scenario (HMP, JTM, JL), pp. 55–61.
OCSC-2011-AhmadL #learning: Promoting Reflective Learning: The Role of Blogs in the Classroom (RA, WGL), pp. 3–11.
OCSC-2011-PujariK #approach #machine learning #predict #recommendation: A Supervised Machine Learning Link Prediction Approach for Tag Recommendation (MP, RK), pp. 336–344.
OCSC-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.
SIGAda-2011-Booch #ada: Everything i know i learned from ada (GB), pp. 17–18.
CAiSE-2011-DornD #process #self: Supporting Dynamic, People-Driven Processes through Self-learning of Message Flows (CD, SD), pp. 657–671.
ICEIS-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.
ICEIS-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.
ICEIS-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.
ICEIS-v4-2011-Marks #collaboration #learning #student: Students’ Acceptance of E-Group Collaboration Learning (AM), pp. 269–274.
CIKM-2011-ArguelloDC #learning #web: Learning to aggregate vertical results into web search results (JA, FD, JC), pp. 201–210.
CIKM-2011-CoffmanW #keyword #learning #rank #relational: Learning to rank results in relational keyword search (JC, ACW), pp. 1689–1698.
CIKM-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.
CIKM-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.
CIKM-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.
CIKM-2011-GiannopoulosBDS #learning #rank: Learning to rank user intent (GG, UB, TD, TKS), pp. 195–200.
CIKM-2011-KasiviswanathanMBS #detection #learning #taxonomy #topic #using: Emerging topic detection using dictionary learning (SPK, PM, AB, VS), pp. 745–754.
CIKM-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.
CIKM-2011-LiCHLJ #collaboration #learning #online: Collaborative online learning of user generated content (GL, KC, SCHH, WL, RJ), pp. 285–290.
CIKM-2011-LinC #data fusion #learning #query: Query sampling for learning data fusion (TCL, PJC), pp. 141–146.
CIKM-2011-LinLWX #learning #rank: Learning to rank with cross entropy (YL, HL, JW, KX), pp. 2057–2060.
CIKM-2011-LiSZ #feedback: Learning-based relevance feedback for web-based relation completion (ZL, LS, XZ), pp. 1535–1540.
CIKM-2011-LiuCZH #learning #random: Learning conditional random fields with latent sparse features for acronym expansion finding (JL, JC, YZ, YH), pp. 867–872.
CIKM-2011-LiuLH #bound #fault #kernel #learning: Learning kernels with upper bounds of leave-one-out error (YL, SL, YH), pp. 2205–2208.
CIKM-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.
CIKM-2011-OroR #approach #learning #named: SILA: a spatial instance learning approach for deep webpages (EO, MR), pp. 2329–2332.
CIKM-2011-PandeyABHCRZ #behaviour #learning #what: Learning to target: what works for behavioral targeting (SP, MA, AB, AOH, PC, AR, MZ), pp. 1805–1814.
CIKM-2011-QianHCZN #ambiguity #machine learning: Combining machine learning and human judgment in author disambiguation (YnQ, YH, JC, QZ, ZN), pp. 1241–1246.
CIKM-2011-RamanJS #learning #ranking: Structured learning of two-level dynamic rankings (KR, TJ, PS), pp. 291–296.
CIKM-2011-SellamanickamGS #approach #learning #ranking: A pairwise ranking based approach to learning with positive and unlabeled examples (SS, PG, SKS), pp. 663–672.
CIKM-2011-SzummerY #learning #rank: Semi-supervised learning to rank with preference regularization (MS, EY), pp. 269–278.
CIKM-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.
CIKM-2011-UllegaddiV #category theory #learning #query #rank #web: Learning to rank categories for web queries (PU, VV), pp. 2065–2068.
CIKM-2011-WangCWLWO #learning #similarity: Coupled nominal similarity in unsupervised learning (CW, LC, MW, JL, WW, YO), pp. 973–978.
CIKM-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.
CIKM-2011-WangHLCH #learning #recommendation: Learning to recommend questions based on public interest (JW, XH, ZL, WHC, BH), pp. 2029–2032.
CIKM-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.
CIKM-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.
CIKM-2011-YangZKL #how #learning #question #why: Can irrelevant data help semi-supervised learning, why and how? (HY, SZ, IK, MRL), pp. 937–946.
CIKM-2011-YanTLSL #learning #predict: Citation count prediction: learning to estimate future citations for literature (RY, JT, XL, DS, XL), pp. 1247–1252.
CIKM-2011-ZhangYCT #detection: A machine-learned proactive moderation system for auction fraud detection (LZ, JY, WC, BLT), pp. 2501–2504.
CIKM-2011-ZhaoYX #independence #information management #learning #web: Max margin learning on domain-independent web information extraction (BZ, XY, EPX), pp. 1305–1310.
CIKM-2011-ZhuZYGX #learning: Transfer active learning (ZZ, XZ, YY, YFG, XX), pp. 2169–2172.
ECIR-2011-BuffoniTG #ranking: The Importance of the Depth for Text-Image Selection Strategy in Learning-To-Rank (DB, ST, PG), pp. 743–746.
ECIR-2011-HofmannWR #learning #online #rank: Balancing Exploration and Exploitation in Learning to Rank Online (KH, SW, MdR), pp. 251–263.
ECIR-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.
ECIR-2011-MacdonaldO #learning #modelling #ranking: Learning Models for Ranking Aggregates (CM, IO), pp. 517–529.
ECIR-2011-ZhouH #comprehension #learning #natural language #random: Learning Conditional Random Fields from Unaligned Data for Natural Language Understanding (DZ, YH), pp. 283–288.
ICML-2011-BabenkoVDB #learning #multi: Multiple Instance Learning with Manifold Bags (BB, NV, PD, SB), pp. 81–88.
ICML-2011-BabesMLS #learning #multi: Apprenticeship Learning About Multiple Intentions (MB, VNM, KS, MLL), pp. 897–904.
ICML-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.
ICML-2011-BuffoniCGU #learning #standard: Learning Scoring Functions with Order-Preserving Losses and Standardized Supervision (DB, CC, PG, NU), pp. 825–832.
ICML-2011-Bylander #learning #linear #multi #polynomial: Learning Linear Functions with Quadratic and Linear Multiplicative Updates (TB), pp. 505–512.
ICML-2011-ChakrabortyS #learning: Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function’s In-Degree (DC, PS), pp. 737–744.
ICML-2011-ChenPSDC #analysis #learning #process: The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning (BC, GP, GS, DBD, LC), pp. 361–368.
ICML-2011-ChoRI #adaptation #learning #strict: Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines (KC, TR, AI), pp. 105–112.
ICML-2011-DauphinGB #learning #re-engineering #scalability: Large-Scale Learning of Embeddings with Reconstruction Sampling (YD, XG, YB), pp. 945–952.
ICML-2011-DinuzzoOGP #coordination #kernel #learning: Learning Output Kernels with Block Coordinate Descent (FD, CSO, PVG, GP), pp. 49–56.
ICML-2011-DudikLL #evaluation #learning #policy #robust: Doubly Robust Policy Evaluation and Learning (MD, JL, LL), pp. 1097–1104.
ICML-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.
ICML-2011-Gould #learning #linear #markov #random: Max-margin Learning for Lower Linear Envelope Potentials in Binary Markov Random Fields (SG), pp. 193–200.
ICML-2011-GuilloryB #learning: Simultaneous Learning and Covering with Adversarial Noise (AG, JAB), pp. 369–376.
ICML-2011-HarelM #learning #multi: Learning from Multiple Outlooks (MH, SM), pp. 401–408.
ICML-2011-HeL #framework #learning #multi: A Graphbased Framework for Multi-Task Multi-View Learning (JH, RL), pp. 25–32.
ICML-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.
ICML-2011-JawanpuriaNR #kernel #learning #performance #using: Efficient Rule Ensemble Learning using Hierarchical Kernels (PJ, JSN, GR), pp. 161–168.
ICML-2011-KangGS #learning #multi: Learning with Whom to Share in Multi-task Feature Learning (ZK, KG, FS), pp. 521–528.
ICML-2011-KuwadekarN #classification #learning #modelling #relational: Relational Active Learning for Joint Collective Classification Models (AK, JN), pp. 385–392.
ICML-2011-LeeW #identification #learning #online #probability: Manifold Identification of Dual Averaging Methods for Regularized Stochastic Online Learning (SL, SJW), pp. 1121–1128.
ICML-2011-LeNCLPN #learning #on the #optimisation: On optimization methods for deep learning (QVL, JN, AC, AL, BP, AYN), pp. 265–272.
ICML-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.
ICML-2011-LuB #learning #modelling: Learning Mallows Models with Pairwise Preferences (TL, CB), pp. 145–152.
ICML-2011-Maaten #kernel #learning: Learning Discriminative Fisher Kernels (LvdM), pp. 217–224.
ICML-2011-MachartPARG #kernel #learning #probability #rank: Stochastic Low-Rank Kern