Proceedings of the 31st International Conference on Machine Learning, Cycle 2
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Proceedings of the 31st International Conference on Machine Learning, Cycle 2
ICML c2, 2014.

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@proceedings{ICML-c2-2014,
	address       = "Beijing, China",
	ee            = "http://jmlr.org/proceedings/papers/v32/",
	publisher     = "{JMLR.org}",
	series        = "{JMLR Proceedings}",
	title         = "{Proceedings of the 31st International Conference on Machine Learning, Cycle 2}",
	volume        = 32,
	year          = 2014,
}

Contents (225 items)

ICML-c2-2014-SunM #geometry #learning #statistics
An Information Geometry of Statistical Manifold Learning (KS, SMM), pp. 1–9.
ICML-c2-2014-ZoghiWMR #bound #problem
Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem (MZ, SW, RM, MdR), pp. 10–18.
ICML-c2-2014-HamidXGD #random
Compact Random Feature Maps (RH, YX, AG, DD), pp. 19–27.
ICML-c2-2014-Kontorovich #algorithm #bound #metric
Concentration in unbounded metric spaces and algorithmic stability (AK), pp. 28–36.
ICML-c2-2014-HsuS
Heavy-tailed regression with a generalized median-of-means (DH, SS), pp. 37–45.
ICML-c2-2014-ValkoMKK #graph
Spectral Bandits for Smooth Graph Functions (MV, RM, BK, TK), pp. 46–54.
ICML-c2-2014-ZhaoMXZZ #analysis #component #robust
Robust Principal Component Analysis with Complex Noise (QZ, DM, ZX, WZ, LZ), pp. 55–63.
ICML-c2-2014-HuangCG #estimation #scalability
Scalable Semidefinite Relaxation for Maximum A Posterior Estimation (QXH, YC, LJG), pp. 64–72.
ICML-c2-2014-MuHWG #bound
Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery (CM, BH, JW, DG), pp. 73–81.
ICML-c2-2014-DasL #automation #interactive
Automated inference of point of view from user interactions in collective intelligence venues (SD, AL), pp. 82–90.
ICML-c2-2014-WangLLFDY #matrix
Rank-One Matrix Pursuit for Matrix Completion (ZW, MJL, ZL, WF, HD, JY), pp. 91–99.
ICML-c2-2014-ChenGH
Near-Optimal Joint Object Matching via Convex Relaxation (YC, LJG, QXH), pp. 100–108.
ICML-c2-2014-MalioutovS
Convex Total Least Squares (DM, NS), pp. 109–117.
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-YuanLZ #optimisation
Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization (XY, PL, TZ), pp. 127–135.
ICML-c2-2014-HonorioJ #consistency #framework
A Unified Framework for Consistency of Regularized Loss Minimizers (JH, TSJ), pp. 136–144.
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-SinglaBBKK #education
Near-Optimally Teaching the Crowd to Classify (AS, IB, GB, AK, AK), pp. 154–162.
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-MaryPN #algorithm #evaluation
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques (JM, PP, ON), pp. 172–180.
ICML-c2-2014-TamarMX #approximate #robust #scalability #using
Scaling Up Robust MDPs using Function Approximation (AT, SM, HX), pp. 181–189.
ICML-c2-2014-PingLI
Marginal Structured SVM with Hidden Variables (WP, QL, ATI), pp. 190–198.
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-GalG #parallel #process #using
Pitfalls in the use of Parallel Inference for the Dirichlet Process (YG, ZG), pp. 208–216.
ICML-c2-2014-ZhouCL #crowdsourcing #identification #multi
Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing (YZ, XC, JL), pp. 217–225.
ICML-c2-2014-BengioLAY #generative #network #probability
Deep Generative Stochastic Networks Trainable by Backprop (YB, EL, GA, JY), pp. 226–234.
ICML-c2-2014-WangLYFWY #algorithm #modelling #parallel #scalability
A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models (JW, QL, SY, WF, PW, JY), pp. 235–243.
ICML-c2-2014-ChenX #modelling #statistics
Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting (YC, JX), pp. 244–252.
ICML-c2-2014-ContalPV #optimisation #process
Gaussian Process Optimization with Mutual Information (EC, VP, NV), pp. 253–261.
ICML-c2-2014-ZhouLPM
Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy (DZ, QL, JCP, CM), pp. 262–270.
ICML-c2-2014-NiepertD #modelling
Exchangeable Variable Models (MN, PMD), pp. 271–279.
ICML-c2-2014-Ben-DavidH #clustering
Clustering in the Presence of Background Noise (SBD, NH), pp. 280–288.
ICML-c2-2014-LiuZWY
Safe Screening with Variational Inequalities and Its Application to Lasso (JL, ZZ, JW, JY), pp. 289–297.
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.
ICML-c2-2014-EstrachSL
Signal recovery from Pooling Representations (JBE, AS, YL), pp. 307–315.
ICML-c2-2014-BrunskillL #learning
PAC-inspired Option Discovery in Lifelong Reinforcement Learning (EB, LL), pp. 316–324.
ICML-c2-2014-LinDH0 #classification #encoding #multi
Multi-label Classification via Feature-aware Implicit Label Space Encoding (ZL, GD, MH, JW), pp. 325–333.
ICML-c2-2014-BratieresQNG #graph #grid #predict #process #scalability
Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications (SB, NQ, SN, ZG), pp. 334–342.
ICML-c2-2014-ClemenconR #ranking
Anomaly Ranking as Supervised Bipartite Ranking (SC, SR), pp. 343–351.
ICML-c2-2014-CarlssonMRS #clustering #network #symmetry
Hierarchical Quasi-Clustering Methods for Asymmetric Networks (GEC, FM, AR, SS), pp. 352–360.
ICML-c2-2014-NakanoIKYU #process
Rectangular Tiling Process (MN, KI, AK, TY, NU), pp. 361–369.
ICML-c2-2014-WangSSMK #learning #metric
Two-Stage Metric Learning (JW, KS, FS, SMM, AK), pp. 370–378.
ICML-c2-2014-Hernandez-LobatoHG #matrix #modelling #probability #scalability
Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices (JMHL, NH, ZG), pp. 379–387.
ICML-c2-2014-YangLR #linear
Elementary Estimators for High-Dimensional Linear Regression (EY, ACL, PDR), pp. 388–396.
ICML-c2-2014-YangLR14a #matrix
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments (EY, ACL, PDR), pp. 397–405.
ICML-c2-2014-FangCL #graph #learning
Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically (YF, KCCC, HWL), pp. 406–414.
ICML-c2-2014-LiZ0 #learning #multi
Bayesian Max-margin Multi-Task Learning with Data Augmentation (CL, JZ, JC), pp. 415–423.
ICML-c2-2014-QinLJ #learning #optimisation
Sparse Reinforcement Learning via Convex Optimization (ZQ, WL, FJ), pp. 424–432.
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-SuGR #network #predict
Structured Prediction of Network Response (HS, AG, JR), pp. 442–450.
ICML-c2-2014-TaylorGP #analysis #approximate #linear #programming
An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy (GT, CG, DP), pp. 451–459.
ICML-c2-2014-YangPK #equivalence #optimisation
Optimization Equivalence of Divergences Improves Neighbor Embedding (ZY, JP, SK), pp. 460–468.
ICML-c2-2014-LiuWRBS #algorithm #coordination #parallel #probability
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm (JL, SW, CR, VB, SS), pp. 469–477.
ICML-c2-2014-KpotufeSJS #consistency
Consistency of Causal Inference under the Additive Noise Model (SK, ES, DJ, BS), pp. 478–486.
ICML-c2-2014-SchwingHPU #algorithm #convergence #parallel #using
Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm (AGS, TH, MP, RU), pp. 487–495.
ICML-c2-2014-MalekAB #linear #markov #problem #programming #scalability
Linear Programming for Large-Scale Markov Decision Problems (AM, YAY, PLB), pp. 496–504.
ICML-c2-2014-NieHH #linear
Linear Time Solver for Primal SVM (FN, YH, HH), pp. 505–513.
ICML-c2-2014-JunB #memory management #monte carlo #performance
Memory (and Time) Efficient Sequential Monte Carlo (SHJ, ABC), pp. 514–522.
ICML-c2-2014-WangWY #reduction #scalability
Scaling SVM and Least Absolute Deviations via Exact Data Reduction (JW, PW, JY), pp. 523–531.
ICML-c2-2014-LiG #classification #learning #representation #semantics
Latent Semantic Representation Learning for Scene Classification (XL, YG), pp. 532–540.
ICML-c2-2014-AgarwalKKSV #multi #predict #scalability
Least Squares Revisited: Scalable Approaches for Multi-class Prediction (AA, SMK, NK, LS, GV), pp. 541–549.
ICML-c2-2014-AwasthiBV #algorithm #clustering #interactive
Local algorithms for interactive clustering (PA, MFB, KV), pp. 550–558.
ICML-c2-2014-NgoT #modelling #relational
Model-Based Relational RL When Object Existence is Partially Observable (NAV, MT), pp. 559–567.
ICML-c2-2014-SuttonMPH #equivalence #monte carlo
A new Q(λ) with interim forward view and Monte Carlo equivalence (RSS, ARM, DP, HvH), pp. 568–576.
ICML-c2-2014-TorkamaniL #on the #robust
On Robustness and Regularization of Structural Support Vector Machines (MT, DL), pp. 577–585.
ICML-c2-2014-BeijbomSKV #multi
Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting (OB, MJS, DJK, NV), pp. 586–594.
ICML-c2-2014-KirosSZ #modelling #multimodal
Multimodal Neural Language Models (RK, RS, RSZ), pp. 595–603.
ICML-c2-2014-Sohl-DicksteinPG #optimisation #performance #probability #scalability
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods (JSD, BP, SG), pp. 604–612.
ICML-c2-2014-YiCS #linear
Alternating Minimization for Mixed Linear Regression (XY, CC, SS), pp. 613–621.
ICML-c2-2014-KusnerTWA #probability
Stochastic Neighbor Compression (MJK, ST, KQW, KA), pp. 622–630.
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-SongADX #estimation #modelling #multi #parametricity
Nonparametric Estimation of Multi-View Latent Variable Models (LS, AA, BD, BX), pp. 640–648.
ICML-c2-2014-MaddisonT #generative #modelling #source code
Structured Generative Models of Natural Source Code (CJM, DT), pp. 649–657.
ICML-c2-2014-Yi0WJJ #algorithm #clustering
A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data (JY, LZ, JW, RJ, AKJ), pp. 658–666.
ICML-c2-2014-ToulisAR #analysis #linear #modelling #probability #statistics
Statistical analysis of stochastic gradient methods for generalized linear models (PT, EA, JR), pp. 667–675.
ICML-c2-2014-0001MS #random
Coding for Random Projections (PL, MM, AS), pp. 676–684.
ICML-c2-2014-CuturiD #performance
Fast Computation of Wasserstein Barycenters (MC, AD), pp. 685–693.
ICML-c2-2014-JohanssonJDB #geometry #graph #kernel #using
Global graph kernels using geometric embeddings (FJ, VJ, DPD, CB), pp. 694–702.
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-VinnikovS #component #independence
K-means recovers ICA filters when independent components are sparse (AV, SSS), pp. 712–720.
ICML-c2-2014-SunIM #classification #learning #linear
Learning Mixtures of Linear Classifiers (YS, SI, AM), pp. 721–729.
ICML-c2-2014-WangST #statistics
The Falling Factorial Basis and Its Statistical Applications (YXW, AJS, RJT), pp. 730–738.
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-ArgyriouD #theorem
A Unifying View of Representer Theorems (AA, FD), pp. 748–756.
ICML-c2-2014-GentileLZ #clustering #online
Online Clustering of Bandits (CG, SL, GZ), pp. 757–765.
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-NguyenMVEB #analysis #correlation #multi
Multivariate Maximal Correlation Analysis (HVN, EM, JV, PE, KB), pp. 775–783.
ICML-c2-2014-FujiwaraI #performance
Efficient Label Propagation (YF, GI), pp. 784–792.
ICML-c2-2014-DaneshmandGSS #algorithm #complexity #network
Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm (HD, MGR, LS, BS), pp. 793–801.
ICML-c2-2014-YanLXH #predict
Coupled Group Lasso for Web-Scale CTR Prediction in Display Advertising (LY, WJL, GRX, DH), pp. 802–810.
ICML-c2-2014-NovikovROV
Putting MRFs on a Tensor Train (AN, AR, AO, DV), pp. 811–819.
ICML-c2-2014-0005YJ #algorithm #performance #robust
Efficient Algorithms for Robust One-bit Compressive Sensing (LZ, JY, RJ), pp. 820–828.
ICML-c2-2014-LevineK #learning #network #optimisation #policy
Learning Complex Neural Network Policies with Trajectory Optimization (SL, VK), pp. 829–837.
ICML-c2-2014-ZhangDW #approximate #nearest neighbour
Composite Quantization for Approximate Nearest Neighbor Search (TZ, CD, JW), pp. 838–846.
ICML-c2-2014-TeradaL
Local Ordinal Embedding (YT, UvL), pp. 847–855.
ICML-c2-2014-AilonKJ
Reducing Dueling Bandits to Cardinal Bandits (NA, ZSK, TJ), pp. 856–864.
ICML-c2-2014-XuTXR #reduction
Large-margin Weakly Supervised Dimensionality Reduction (CX, DT, CX, YR), pp. 865–873.
ICML-c2-2014-ChakrabartiFCM #multi #network #scalability
Joint Inference of Multiple Label Types in Large Networks (DC, SF, JC, SAM), pp. 874–882.
ICML-c2-2014-KarninH #linear
Hard-Margin Active Linear Regression (ZSK, EH), pp. 883–891.
ICML-c2-2014-KontorovichW #multi #nearest neighbour
Maximum Margin Multiclass Nearest Neighbors (AK, RW), pp. 892–900.
ICML-c2-2014-LinAKLC #combinator #feedback #game studies #linear #monitoring
Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications (TL, BDA, RDK, JL, WC), pp. 901–909.
ICML-c2-2014-ReyRF
Sparse meta-Gaussian information bottleneck (MR, VR, TJF), pp. 910–918.
ICML-c2-2014-KrishnamurthyKPW #estimation #parametricity
Nonparametric Estimation of Renyi Divergence and Friends (AK, KK, BP, LAW), pp. 919–927.
ICML-c2-2014-WangL #estimation #metric #robust
Robust Inverse Covariance Estimation under Noisy Measurements (JKW, SdL), pp. 928–936.
ICML-c2-2014-GardnerKZWC #constraints #difference #optimisation
Bayesian Optimization with Inequality Constraints (JRG, MJK, ZEX, KQW, JC), pp. 937–945.
ICML-c2-2014-YuKGC
Circulant Binary Embedding (FXY, SK, YG, SFC), pp. 946–954.
ICML-c2-2014-LiuZBP #dependence #modelling #multi #testing #visual notation
Multiple Testing under Dependence via Semiparametric Graphical Models (JL, CZ, ESB, DP), pp. 955–963.
ICML-c2-2014-TuZWQ #analysis #scalability
Making Fisher Discriminant Analysis Scalable (BT, ZZ, SW, HQ), pp. 964–972.
ICML-c2-2014-KimO #process #scalability
Hierarchical Dirichlet Scaling Process (DK, AHO), pp. 973–981.
ICML-c2-2014-SatoN #analysis #approximate #equation #probability #process #using
Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process (IS, HN), pp. 982–990.
ICML-c2-2014-PentinaL #bound #learning
A PAC-Bayesian bound for Lifelong Learning (AP, CHL), pp. 991–999.
ICML-c2-2014-ShamirS0 #approximate #distributed #optimisation #using
Communication-Efficient Distributed Optimization using an Approximate Newton-type Method (OS, NS, TZ), pp. 1000–1008.
ICML-c2-2014-HarelMEC #concept #detection
Concept Drift Detection Through Resampling (MH, SM, REY, KC), pp. 1009–1017.
ICML-c2-2014-GleichM #algorithm #approximate #case study
Anti-differentiating approximation algorithms: A case study with min-cuts, spectral, and flow (DG, MWM), pp. 1018–1025.
ICML-c2-2014-BenavoliCMZR #process
A Bayesian Wilcoxon signed-rank test based on the Dirichlet process (AB, GC, FM, MZ, FR), pp. 1026–1034.
ICML-c2-2014-RavanbakhshSFG #graph #problem
Min-Max Problems on Factor Graphs (S(R, CS, BJF, RG), pp. 1035–1043.
ICML-c2-2014-AhnSW #distributed #probability
Distributed Stochastic Gradient MCMC (SA, BS, MW), pp. 1044–1052.
ICML-c2-2014-Cherian #nearest neighbour #using
Nearest Neighbors Using Compact Sparse Codes (AC), pp. 1053–1061.
ICML-c2-2014-NieYH #analysis #component #robust
Optimal Mean Robust Principal Component Analysis (FN, JY, HH), pp. 1062–1070.
ICML-c2-2014-Busa-FeketeHS #elicitation #modelling #rank #statistics #using
Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows (RBF, EH, BS), pp. 1071–1079.
ICML-c2-2014-AhmedTBZDKB #detection #random
Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations (BA, TT, KB, YZ, OD, RK, CEB), pp. 1080–1088.
ICML-c2-2014-ScholzLIW #object-oriented
A Physics-Based Model Prior for Object-Oriented MDPs (JS, ML, CLIJ, DW), pp. 1089–1097.
ICML-c2-2014-SuzumuraOST #algorithm #robust
Outlier Path: A Homotopy Algorithm for Robust SVM (SS, KO, MS, IT), pp. 1098–1106.
ICML-c2-2014-WangY #crowdsourcing
Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data (NW, DYY), pp. 1107–1115.
ICML-c2-2014-SatoKN #analysis #normalisation
Latent Confusion Analysis by Normalized Gamma Construction (IS, HK, HN), pp. 1116–1124.
ICML-c2-2014-DefazioDC #big data #incremental #named #performance #problem
Finito: A faster, permutable incremental gradient method for big data problems (AD, JD, TSC), pp. 1125–1133.
ICML-c2-2014-CortesKM #predict
Ensemble Methods for Structured Prediction (CC, VK, MM), pp. 1134–1142.
ICML-c2-2014-RomanoBNV #clustering #standard
Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance (SR, JB, XVN, KV), pp. 1143–1151.
ICML-c2-2014-PachecoZBS
Preserving Modes and Messages via Diverse Particle Selection (JP, SZ, MJB, EBS), pp. 1152–1160.
ICML-c2-2014-WangRRCC #design #metric
Nonlinear Information-Theoretic Compressive Measurement Design (LW, AR, MRDR, ARC, LC), pp. 1161–1169.
ICML-c2-2014-GaboardiAHRW #query
Dual Query: Practical Private Query Release for High Dimensional Data (MG, EJGA, JH, AR, ZSW), pp. 1170–1178.
ICML-c2-2014-CortesMS
Deep Boosting (CC, MM, US), pp. 1179–1187.
ICML-c2-2014-LeM #distributed #documentation
Distributed Representations of Sentences and Documents (QVL, TM), pp. 1188–1196.
ICML-c2-2014-McGibbonRSKP #comprehension #markov #modelling
Understanding Protein Dynamics with L1-Regularized Reversible Hidden Markov Models (RM, BR, MS, GK, VSP), pp. 1197–1205.
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-WestonWY
Affinity Weighted Embedding (JW, RJW, HY), pp. 1215–1223.
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-EbanMG #classification
Discrete Chebyshev Classifiers (EE, EM, AG), pp. 1233–1241.
ICML-c2-2014-GregorDMBW #network
Deep AutoRegressive Networks (KG, ID, AM, CB, DW), pp. 1242–1250.
ICML-c2-2014-SunZZ #analysis #convergence
A Convergence Rate Analysis for LogitBoost, MART and Their Variant (PS, TZ, JZ), pp. 1251–1259.
ICML-c2-2014-HeinemannG #modelling #visual notation
Inferning with High Girth Graphical Models (UH, AG), pp. 1260–1268.
ICML-c2-2014-MengEH #learning #modelling #visual notation
Learning Latent Variable Gaussian Graphical Models (ZM, BE, AOHI), pp. 1269–1277.
ICML-c2-2014-RezendeMW #approximate #generative #modelling #probability
Stochastic Backpropagation and Approximate Inference in Deep Generative Models (DJR, SM, DW), pp. 1278–1286.
ICML-c2-2014-SeldinS #algorithm #probability
One Practical Algorithm for Both Stochastic and Adversarial Bandits (YS, AS), pp. 1287–1295.
ICML-c2-2014-GiesenLW #kernel #performance #robust
Robust and Efficient Kernel Hyperparameter Paths with Guarantees (JG, SL, PW), pp. 1296–1304.
ICML-c2-2014-WangHS #learning
Active Transfer Learning under Model Shift (XW, TKH, JS), pp. 1305–1313.
ICML-c2-2014-Scherrer #approximate #comparison #policy
Approximate Policy Iteration Schemes: A Comparison (BS), pp. 1314–1322.
ICML-c2-2014-LinK #constraints #learning #performance #representation
Stable and Efficient Representation Learning with Nonnegativity Constraints (THL, HTK), pp. 1323–1331.
ICML-c2-2014-GrandeWH #learning #performance #process
Sample Efficient Reinforcement Learning with Gaussian Processes (RCG, TJW, JPH), pp. 1332–1340.
ICML-c2-2014-AnarakiH #memory management #performance #random
Memory and Computation Efficient PCA via Very Sparse Random Projections (FPA, SMH), pp. 1341–1349.
ICML-c2-2014-MannMM
Time-Regularized Interrupting Options (TRIO) (TAM, DJM, SM), pp. 1350–1358.
ICML-c2-2014-Lopez-PazSSGS #analysis #component #random
Randomized Nonlinear Component Analysis (DLP, SS, AJS, ZG, BS), pp. 1359–1367.
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-NiuDPS #approximate #learning #multi
Transductive Learning with Multi-class Volume Approximation (GN, BD, MCdP, MS), pp. 1377–1385.
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-Chapados #effectiveness #modelling
Effective Bayesian Modeling of Groups of Related Count Time Series (NC), pp. 1395–1403.
ICML-c2-2014-BartunovV #distance #process
Variational Inference for Sequential Distance Dependent Chinese Restaurant Process (SB, DV), pp. 1404–1412.
ICML-c2-2014-LindermanA #network #process
Discovering Latent Network Structure in Point Process Data (SWL, RPA), pp. 1413–1421.
ICML-c2-2014-ChwialkowskiG #independence #kernel #process #random
A Kernel Independence Test for Random Processes (KC, AG), pp. 1422–1430.
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-AziziAG #composition #learning #network
Learning Modular Structures from Network Data and Node Variables (EA, EA, JEG), pp. 1440–1448.
ICML-c2-2014-MukutaH #analysis #canonical #correlation #probability
Probabilistic Partial Canonical Correlation Analysis (YM, TH), pp. 1449–1457.
ICML-c2-2014-BellemareVT
Skip Context Tree Switching (MGB, JV, ET), pp. 1458–1466.
ICML-c2-2014-ToshD #bound
Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians (CT, SD), pp. 1467–1475.
ICML-c2-2014-ChenWSB
Marginalized Denoising Auto-encoders for Nonlinear Representations (MC, KQW, FS, YB), pp. 1476–1484.
ICML-c2-2014-BarberW #difference #equation #estimation #process
Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations (DB, YW), pp. 1485–1493.
ICML-c2-2014-WeiIB #multi #performance
Fast Multi-stage Submodular Maximization (KW, RKI, JAB), pp. 1494–1502.
ICML-c2-2014-SchoenauerASS #feedback #programming
Programming by Feedback (MS, RA, MS, JCS), pp. 1503–1511.
ICML-c2-2014-Hernandez-LobatoHG14a #matrix #probability
Probabilistic Matrix Factorization with Non-random Missing Data (JMHL, NH, ZG), pp. 1512–1520.
ICML-c2-2014-DworkinKN
Pursuit-Evasion Without Regret, with an Application to Trading (LD, MK, YN), pp. 1521–1529.
ICML-c2-2014-KurrasLB #geometry #graph
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation (SK, UvL, GB), pp. 1530–1538.
ICML-c2-2014-TanTWVP #matrix
Riemannian Pursuit for Big Matrix Recovery (MT, IWT, LW, BV, SJP), pp. 1539–1547.
ICML-c2-2014-LefakisF #programming
Dynamic Programming Boosting for Discriminative Macro-Action Discovery (LL, FF), pp. 1548–1556.
ICML-c2-2014-AzarLB #correlation #feedback #online #optimisation #probability
Online Stochastic Optimization under Correlated Bandit Feedback (MGA, AL, EB), pp. 1557–1565.
ICML-c2-2014-ChenLX #clustering #graph #nondeterminism
Weighted Graph Clustering with Non-Uniform Uncertainties (YC, SHL, HX), pp. 1566–1574.
ICML-c2-2014-Thomas14a #convergence #named
GeNGA: A Generalization of Natural Gradient Ascent with Positive and Negative Convergence Results (PT), pp. 1575–1583.
ICML-c2-2014-BaiLS #classification #framework #online
A Bayesian Framework for Online Classifier Ensemble (QB, HL, SS), pp. 1584–1592.
ICML-c2-2014-SteinhardtL14a #adaptation #algorithm
Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm (JS, PL), pp. 1593–1601.
ICML-c2-2014-LiuSD #approximate #modelling #visual notation
Gaussian Approximation of Collective Graphical Models (LPL, DS, TGD), pp. 1602–1610.
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-KondorTG #matrix #multi
Multiresolution Matrix Factorization (RK, NT, VG), pp. 1620–1628.
ICML-c2-2014-LiuD #learning #problem #set
Learnability of the Superset Label Learning Problem (LPL, TGD), pp. 1629–1637.
ICML-c2-2014-AgarwalHKLLS #algorithm #performance
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits (AA, DH, SK, JL, LL, RES), pp. 1638–1646.
ICML-c2-2014-MittelmanKSL #strict
Structured Recurrent Temporal Restricted Boltzmann Machines (RM, BK, SS, HL), pp. 1647–1655.
ICML-c2-2014-MinskerSLD #robust #scalability
Scalable and Robust Bayesian Inference via the Median Posterior (SM, SS, LL, DBD), pp. 1656–1664.
ICML-c2-2014-SejdinovicSGAG #adaptation #kernel
Kernel Adaptive Metropolis-Hastings (DS, HS, MLG, CA, AG), pp. 1665–1673.
ICML-c2-2014-SnoekSZA #optimisation
Input Warping for Bayesian Optimization of Non-Stationary Functions (JS, KS, RSZ, RPA), pp. 1674–1682.
ICML-c2-2014-ChenFG #monte carlo #probability
Stochastic Gradient Hamiltonian Monte Carlo (TC, EBF, CG), pp. 1683–1691.
ICML-c2-2014-TrigeorgisBZS #learning
A Deep Semi-NMF Model for Learning Hidden Representations (GT, KB, SZ, BWS), pp. 1692–1700.
ICML-c2-2014-ZhangK #distributed #optimisation
Asynchronous Distributed ADMM for Consensus Optimization (RZ, JTK), pp. 1701–1709.
ICML-c2-2014-QuattoniBCG #sequence
Spectral Regularization for Max-Margin Sequence Tagging (AQ, BB, XC, AG), pp. 1710–1718.
ICML-c2-2014-PandeyD #learning #network
Learning by Stretching Deep Networks (GP, AD), pp. 1719–1727.
ICML-c2-2014-AsterisPD
Nonnegative Sparse PCA with Provable Guarantees (MA, DSP, AGD), pp. 1728–1736.
ICML-c2-2014-SilvaKB #learning
Active Learning of Parameterized Skills (BCdS, GK, AGB), pp. 1737–1745.
ICML-c2-2014-RippelGA #learning #order
Learning Ordered Representations with Nested Dropout (OR, MAG, RPA), pp. 1746–1754.
ICML-c2-2014-CohenW #commutative #learning
Learning the Irreducible Representations of Commutative Lie Groups (TC, MW), pp. 1755–1763.
ICML-c2-2014-GravesJ #network #recognition #speech #towards
Towards End-To-End Speech Recognition with Recurrent Neural Networks (AG, NJ), pp. 1764–1772.
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-KingmaW #performance
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets (DPK, MW), pp. 1782–1790.
ICML-c2-2014-MnihG #learning #network
Neural Variational Inference and Learning in Belief Networks (AM, KG), pp. 1791–1799.
ICML-c2-2014-RaiWGCDC #composition #multi #rank #scalability
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors (PR, YW, SG, GC, DBD, LC), pp. 1800–1808.
ICML-c2-2014-HeaukulaniKG
Beta Diffusion Trees (CH, DAK, ZG), pp. 1809–1817.
ICML-c2-2014-SantosZ #learning
Learning Character-level Representations for Part-of-Speech Tagging (CNdS, BZ), pp. 1818–1826.
ICML-c2-2014-YuKC #algorithm
Saddle Points and Accelerated Perceptron Algorithms (AWY, FKK, JGC), pp. 1827–1835.
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-AminHK #learning
Learning from Contagion (Without Timestamps) (KA, HH, MK), pp. 1845–1853.
ICML-c2-2014-JohnsonW #modelling #probability
Stochastic Variational Inference for Bayesian Time Series Models (MJ, ASW), pp. 1854–1862.
ICML-c2-2014-KoutnikGGS
A Clockwork RNN (JK, KG, FJG, JS), pp. 1863–1871.
ICML-c2-2014-ChagantyL #modelling #using #visual notation
Estimating Latent-Variable Graphical Models using Moments and Likelihoods (ATC, PL), pp. 1872–1880.
ICML-c2-2014-Bhojanapalli0 #matrix
Universal Matrix Completion (SB, PJ), pp. 1881–1889.
ICML-c2-2014-PapailiopoulosMDC #optimisation #rank
Finding Dense Subgraphs via Low-Rank Bilinear Optimization (DSP, IM, AGD, CC), pp. 1890–1898.
ICML-c2-2014-BothaB #composition #modelling #word
Compositional Morphology for Word Representations and Language Modelling (JAB, PB), pp. 1899–1907.
ICML-c2-2014-AndoniPV0 #learning #network
Learning Polynomials with Neural Networks (AA, RP, GV, LZ), pp. 1908–1916.
ICML-c2-2014-GunasekarRG #constraints #exponential #matrix #product line
Exponential Family Matrix Completion under Structural Constraints (SG, PR, JG), pp. 1917–1925.
ICML-c2-2014-BachmanFP #approximate
Sample-based approximate regularization (PB, AMF, DP), pp. 1926–1934.
ICML-c2-2014-PaigeW #compilation #probability #programming language
A Compilation Target for Probabilistic Programming Languages (BP, FW), pp. 1935–1943.
ICML-c2-2014-NeufeldGSS #adaptation #monte carlo
Adaptive Monte Carlo via Bandit Allocation (JN, AG, CS, DS), pp. 1944–1952.
ICML-c2-2014-CelikLL #estimation #network #performance #reduction
Efficient Dimensionality Reduction for High-Dimensional Network Estimation (SC, BAL, SIL), pp. 1953–1961.
ICML-c2-2014-CelikkayaS #markov #probability #process
Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes (EBC, CRS), pp. 1962–1970.
ICML-c2-2014-TitsiasL #probability
Doubly Stochastic Variational Bayes for non-Conjugate Inference (MKT, MLG), pp. 1971–1979.
ICML-c2-2014-LimL #learning #metric #performance #ranking
Efficient Learning of Mahalanobis Metrics for Ranking (DL, GRGL), pp. 1980–1988.
ICML-c2-2014-0001NKA #estimation #probability
GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare (AA, HN, SK, SA), pp. 1989–1997.
ICML-c2-2014-KnowlesGP #infinity #metric #normalisation #random #using
A reversible infinite HMM using normalised random measures (DAK, ZG, KP), pp. 1998–2006.
ICML-c2-2014-HaeffeleYV #algorithm #image #matrix #rank
Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing (BDH, EY, RV), pp. 2007–2015.
ICML-c2-2014-DuLBS #information management #learning #network
Influence Function Learning in Information Diffusion Networks (ND, YL, MFB, LS), pp. 2016–2024.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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