Proceedings of the 30th International Conference on Machine Learning, Cycle 3
ICML c3, 2013.

@proceedings{ICML-c3-2013,
	address       = "Atlanta, Georgia, USA",
	ee            = "http://jmlr.org/proceedings/papers/v28/",
	publisher     = "{JMLR.org}",
	series        = "{JMLR Proceedings}",
	title         = "{Proceedings of the 30th International Conference on Machine Learning, Cycle 3}",
	volume        = 28,
	year          = 2013,
}

Contents (167 items)

49 ×#learning
21 ×#multi
14 ×#performance
12 ×#algorithm
11 ×#classification
11 ×#modelling
9 ×#kernel
8 ×#on the
7 ×#network
7 ×#optimisation

ICML-c3-2013-LevineK #policy

Guided Policy Search (SL, VK), pp. 1–9.

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-SzorenyiBHOJK #algorithm #distributed #probability

Gossip-based distributed stochastic bandit algorithms (BS, RBF, IH, RO, MJ, BK), pp. 19–27.

ICML-c3-2013-LattimoreHS #learning

The Sample-Complexity of General Reinforcement Learning (TL, MH, PS), pp. 28–36.

ICML-c3-2013-ZweigW #learning

Hierarchical Regularization Cascade for Joint Learning (AZ, DW), pp. 37–45.

ICML-c3-2013-CortesMR #classification #kernel #multi

Multi-Class Classification with Maximum Margin Multiple Kernel (CC, MM, AR), pp. 46–54.

ICML-c3-2013-GrosshansSBS #game studies #problem

Bayesian Games for Adversarial Regression Problems (MG, CS, MB, TS), pp. 55–63.

ICML-c3-2013-ChenLZ #crowdsourcing #policy

Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing (XC, QL, DZ), pp. 64–72.

ICML-c3-2013-KolarLX #estimation #markov #multi #network

Markov Network Estimation From Multi-attribute Data (MK, HL, EPX), pp. 73–81.

ICML-c3-2013-ZhangHSL #learning #multi #named

MILEAGE: Multiple Instance LEArning with Global Embedding (DZ, JH, LS, RDL), pp. 82–90.

ICML-c3-2013-0002YY #linear

Guaranteed Sparse Recovery under Linear Transformation (JL, LY, JY), pp. 91–99.

ICML-c3-2013-MemisevicE #invariant #learning #problem

Learning invariant features by harnessing the aperture problem (RM, GE), pp. 100–108.

ICML-c3-2013-WauthierJJ #performance #ranking

Efficient Ranking from Pairwise Comparisons (FLW, MIJ, NJ), pp. 109–117.

ICML-c3-2013-0002T #kernel #learning

Differentially Private Learning with Kernels (PJ, AT), pp. 118–126.

ICML-c3-2013-AgrawalG #linear

Thompson Sampling for Contextual Bandits with Linear Payoffs (SA, NG), pp. 127–135.

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-KolmogorovT #algorithm #sequence

Inference algorithms for pattern-based CRFs on sequence data (RT, VK), pp. 145–153.

ICML-c3-2013-GopiN0N

One-Bit Compressed Sensing: Provable Support and Vector Recovery (SG, PN, PJ, AVN), pp. 154–162.

ICML-c3-2013-TangSH

Tensor Analyzers (YT, RS, GEH), pp. 163–171.

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-JunZSR #learning

Learning from Human-Generated Lists (KSJ, X(Z, BS, TTR), pp. 181–189.

ICML-c3-2013-WangK #algorithm #energy #performance

A Fast and Exact Energy Minimization Algorithm for Cycle MRFs (HW, DK), pp. 190–198.

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-BryanM #interactive #performance

An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation (NJB, GJM), pp. 208–216.

ICML-c3-2013-Lopes

Estimating Unknown Sparsity in Compressed Sensing (ML), pp. 217–225.

ICML-c3-2013-BroderickKJ #named

MAD-Bayes: MAP-based Asymptotic Derivations from Bayes (TB, BK, MIJ), pp. 226–234.

ICML-c3-2013-PeharzTP #generative #network

The Most Generative Maximum Margin Bayesian Networks (RP, ST, FP), pp. 235–243.

ICML-c3-2013-LeSS #named

Fastfood — Computing Hilbert Space Expansions in loglinear time (QVL, TS, AJS), pp. 244–252.

ICML-c3-2013-ChattopadhyayFDPY #learning

Joint Transfer and Batch-mode Active Learning (RC, WF, ID, SP, JY), pp. 253–261.

ICML-c3-2013-QiG #message passing

Message passing with l1 penalized KL minimization (YQ, YG), pp. 262–270.

ICML-c3-2013-Cuturid

Mean Reversion with a Variance Threshold (MC, Ad), pp. 271–279.

ICML-c3-2013-LakshminarayananRT #top-down

Top-down particle filtering for Bayesian decision trees (BL, DMR, YWT), pp. 280–288.

ICML-c3-2013-BalasubramanianYL #learning

Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations (KB, KY, GL), pp. 289–297.

ICML-c3-2013-WangNH #learning #robust #self

Robust and Discriminative Self-Taught Learning (HW, FN, HH), pp. 298–306.

ICML-c3-2013-PirottaRPC #policy

Safe Policy Iteration (MP, MR, AP, DC), pp. 307–315.

ICML-c3-2013-IshtevaPS #order #using

Unfolding Latent Tree Structures using 4th Order Tensors (MI, HP, LS), pp. 316–324.

ICML-c3-2013-ZemelWSPD #learning

Learning Fair Representations (RSZ, YW, KS, TP, CD), pp. 325–333.

ICML-c3-2013-SongIPXP #composition #modelling #visual notation

Hierarchical Tensor Decomposition of Latent Tree Graphical Models (LS, MI, APP, EPX, HP), pp. 334–342.

ICML-c3-2013-SchaulZL #learning

No more pesky learning rates (TS, SZ, YL), pp. 343–351.

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-SeijenS

Planning by Prioritized Sweeping with Small Backups (HvS, RSS), pp. 361–369.

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-DalalyanHMS #learning #modelling #programming

Learning Heteroscedastic Models by Convex Programming under Group Sparsity (ASD, MH, KM, JS), pp. 379–387.

ICML-c3-2013-ZhangZWKYM #kernel

Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels (KZ, VWZ, QW, JTYK, QY, IM), pp. 388–395.

ICML-c3-2013-ZhuLM #algorithm #clustering

A Local Algorithm for Finding Well-Connected Clusters (ZAZ, SL, VSM), pp. 396–404.

ICML-c3-2013-BiK #classification #multi #performance

Efficient Multi-label Classification with Many Labels (WB, JTYK), pp. 405–413.

ICML-c3-2013-ChenC #matrix

Spectral Compressed Sensing via Structured Matrix Completion (YC, YC), pp. 414–422.

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-Cho #image

Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images (KC), pp. 432–440.

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-BaktashmotlaghHBLS #analysis #classification #video

Non-Linear Stationary Subspace Analysis with Application to Video Classification (MB, MTH, AB, BCL, MS), pp. 450–458.

ICML-c3-2013-HonorioJ #bound #exponential #fault

Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy (JH, TSJ), pp. 459–467.

ICML-c3-2013-CovielloMCL #exclamation #performance

That was fast! Speeding up NN search of high dimensional distributions (EC, AM, ABC, GRGL), pp. 468–476.

ICML-c3-2013-VladymyrovC #performance

Entropic Affinities: Properties and Efficient Numerical Computation (MV, MÁCP), pp. 477–485.

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-TamarCM #difference

Temporal Difference Methods for the Variance of the Reward To Go (AT, DDC, SM), pp. 495–503.

ICML-c3-2013-YuLKJC #learning

∝SVM for Learning with Label Proportions (FXY, DL, SK, TJ, SFC), pp. 504–512.

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-MineiroK

Loss-Proportional Subsampling for Subsequent ERM (PM, NK), pp. 522–530.

ICML-c3-2013-Meng #random #scalability

Scalable Simple Random Sampling and Stratified Sampling (XM), pp. 531–539.

ICML-c3-2013-Cheng #learning #similarity

Riemannian Similarity Learning (LC), pp. 540–548.

ICML-c3-2013-JiaVD #on the

On Compact Codes for Spatially Pooled Features (YJ, OV, TD), pp. 549–557.

ICML-c3-2013-WuHG #modelling #multi

Dynamic Covariance Models for Multivariate Financial Time Series (YW, JMHL, ZG), pp. 558–566.

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-YoshiiTMG #infinity

Infinite Positive Semidefinite Tensor Factorization for Source Separation of Mixture Signals (KY, RT, DM, MG), pp. 576–584.

ICML-c3-2013-YangX #algorithm #robust

A Unified Robust Regression Model for Lasso-like Algorithms (WY, HX), pp. 585–593.

ICML-c3-2013-AppelFDP

Quickly Boosting Decision Trees — Pruning Underachieving Features Early (RA, TJF, PD, PP), pp. 594–602.

ICML-c3-2013-MenonNAC #algorithm #classification #consistency #on the #statistics

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance (AKM, HN, SA, SC), pp. 603–611.

ICML-c3-2013-ChuangGMH #topic

Topic Model Diagnostics: Assessing Domain Relevance via Topical Alignment (JC, SG, CDM, JH), pp. 612–620.

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-HuangS #learning #markov #modelling

Spectral Learning of Hidden Markov Models from Dynamic and Static Data (TKH, JGS), pp. 630–638.

ICML-c3-2013-HwangGS #categorisation #semantics #visual notation

Analogy-preserving Semantic Embedding for Visual Object Categorization (SJH, KG, FS), pp. 639–647.

ICML-c3-2013-Izbicki #algebra #approach #classification #online #parallel #performance

Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training (MI), pp. 648–656.

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-Gomez-RodriguezLS #modelling

Modeling Information Propagation with Survival Theory (MGR, JL, BS), pp. 666–674.

ICML-c3-2013-DekelH

Better Rates for Any Adversarial Deterministic MDP (OD, EH), pp. 675–683.

ICML-c3-2013-DimitrakakisT #learning

ABC Reinforcement Learning (CD, NT), pp. 684–692.

ICML-c3-2013-DurrantK #bound #classification #fault

Sharp Generalization Error Bounds for Randomly-projected Classifiers (RJD, AK), pp. 693–701.

ICML-c3-2013-KontorovichNW #learning #on the

On learning parametric-output HMMs (AK, BN, RW), pp. 702–710.

ICML-c3-2013-WeinshallLH #topic #word

LDA Topic Model with Soft Assignment of Descriptors to Words (DW, GL, DH), pp. 711–719.

ICML-c3-2013-KamyshanskaM #on the

On autoencoder scoring (HK, RM), pp. 720–728.

ICML-c3-2013-Chatzis #infinity

Infinite Markov-Switching Maximum Entropy Discrimination Machines (SC), pp. 729–737.

ICML-c3-2013-GermainHLM #adaptation #approach #classification #linear

A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers (PG, AH, FL, EM), pp. 738–746.

ICML-c3-2013-PapailiopoulosDK #approximate #rank

Sparse PCA through Low-rank Approximations (DSP, AGD, SK), pp. 747–755.

ICML-c3-2013-ShenderL #trade-off

Computation-Risk Tradeoffs for Covariance-Thresholded Regression (DS, JDL), pp. 756–764.

ICML-c3-2013-MalioutovV #learning

Exact Rule Learning via Boolean Compressed Sensing (DMM, KRV), pp. 765–773.

ICML-c3-2013-ChenCM #robust

Robust Sparse Regression under Adversarial Corruption (YC, CC, SM), pp. 774–782.

ICML-c3-2013-Mairal #first-order #optimisation

Optimization with First-Order Surrogate Functions (JM), pp. 783–791.

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-LongS #classification #consistency #multi

Consistency versus Realizable H-Consistency for Multiclass Classification (PML, RAS), pp. 801–809.

ICML-c3-2013-SabatoK #multi

Feature Multi-Selection among Subjective Features (SS, AK), pp. 810–818.

ICML-c3-2013-ZhangSMW #adaptation

Domain Adaptation under Target and Conditional Shift (KZ, BS, KM, ZW), pp. 819–827.

ICML-c3-2013-LondonHTG #predict

Collective Stability in Structured Prediction: Generalization from One Example (BL, BH, BT, LG), pp. 828–836.

ICML-c3-2013-RamanJSS #learning

Stable Coactive Learning via Perturbation (KR, TJ, PS, TS), pp. 837–845.

ICML-c3-2013-WangWBLT #learning #multi #taxonomy

Max-Margin Multiple-Instance Dictionary Learning (XW, BW, XB, WL, ZT), pp. 846–854.

ICML-c3-2013-IyerJB #optimisation #performance

Fast Semidifferential-based Submodular Function Optimization (RKI, SJ, JAB), pp. 855–863.

ICML-c3-2013-GonenKK #kernel #matrix

Kernelized Bayesian Matrix Factorization (MG, SAK, SK), pp. 864–872.

ICML-c3-2013-GensD #learning #network

Learning the Structure of Sum-Product Networks (RG, PMD), pp. 873–880.

ICML-c3-2013-YangMM #scalability

Quantile Regression for Large-scale Applications (JY, XM, MWM), pp. 881–887.

ICML-c3-2013-MengM #pipes and filters #robust

Robust Regression on MapReduce (XM, MWM), pp. 888–896.

ICML-c3-2013-OgawaITS

Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines (KO, MI, IT, MS), pp. 897–905.

ICML-c3-2013-GaoJZZ #optimisation

One-Pass AUC Optimization (WG, RJ, SZ, ZHZ), pp. 906–914.

ICML-c3-2013-JancsaryNR #learning #predict

Learning Convex QP Relaxations for Structured Prediction (JJ, SN, CR), pp. 915–923.

ICML-c3-2013-SilverNBWM #concurrent #interactive #learning

Concurrent Reinforcement Learning from Customer Interactions (DS, LN, DB, SW, JM), pp. 924–932.

ICML-c3-2013-SunZ #evaluation #order #representation

Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base Learner (PS, JZ), pp. 933–941.

ICML-c3-2013-KuzborskijO #learning

Stability and Hypothesis Transfer Learning (IK, FO), pp. 942–950.

ICML-c3-2013-KhanAFS #modelling #performance

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models (MEK, AYA, MPF, MWS), pp. 951–959.

ICML-c3-2013-HerlauMS #evolution #modelling #multi #network

Modeling Temporal Evolution and Multiscale Structure in Networks (TH, MM, MNS), pp. 960–968.

ICML-c3-2013-ChenRBT #metric #normalisation #random

Dependent Normalized Random Measures (CC, VR, WLB, YWT), pp. 969–977.

ICML-c3-2013-XuZZ #matrix #performance

Fast Max-Margin Matrix Factorization with Data Augmentation (MX, JZ, BZ), pp. 978–986.

ICML-c3-2013-GuptaAM #image

Natural Image Bases to Represent Neuroimaging Data (AG, MA, AM), pp. 987–994.

ICML-c3-2013-AilonCX #clustering #graph

Breaking the Small Cluster Barrier of Graph Clustering (NA, YC, HX), pp. 995–1003.

ICML-c3-2013-SheldonSKD #approximate #modelling #visual notation

Approximate Inference in Collective Graphical Models (DS, TS, AK, TGD), pp. 1004–1012.

ICML-c3-2013-ReedG #process #scalability

Scaling the Indian Buffet Process via Submodular Maximization (CR, ZG), pp. 1013–1021.

ICML-c3-2013-TakacBRS

Mini-Batch Primal and Dual Methods for SVMs (MT, ASB, PR, NS), pp. 1022–1030.

ICML-c3-2013-HomrighausenM #persistent

The lasso, persistence, and cross-validation (DH, DJM), pp. 1031–1039.

ICML-c3-2013-ChagantyL #linear

Spectral Experts for Estimating Mixtures of Linear Regressions (ATC, PL), pp. 1040–1048.

ICML-c3-2013-OlivaPS

Distribution to Distribution Regression (JBO, BP, JGS), pp. 1049–1057.

ICML-c3-2013-WanZZLF #network #using

Regularization of Neural Networks using DropConnect (LW, MDZ, SZ, YL, RF), pp. 1058–1066.

ICML-c3-2013-WilsonA #kernel #process

Gaussian Process Kernels for Pattern Discovery and Extrapolation (AGW, RPA), pp. 1067–1075.

ICML-c3-2013-XuKHW #learning #representation

Anytime Representation Learning (ZEX, MJK, GH, KQW), pp. 1076–1084.

ICML-c3-2013-NguyenS #algorithm #classification #optimisation

Algorithms for Direct 0-1 Loss Optimization in Binary Classification (TN, SS), pp. 1085–1093.

ICML-c3-2013-Busa-FeketeSCWH #adaptation

Top-k Selection based on Adaptive Sampling of Noisy Preferences (RBF, BS, WC, PW, EH), pp. 1094–1102.

ICML-c3-2013-ErolLRR #parametricity

The Extended Parameter Filter (YE, LL, BR, SJR), pp. 1103–1111.

ICML-c3-2013-BalcanBM #learning #ontology

Exploiting Ontology Structures and Unlabeled Data for Learning (NB, AB, YM), pp. 1112–1120.

ICML-c3-2013-ZhangYJH #optimisation #probability

O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions (LZ, TY, RJ, XH), pp. 1121–1129.

ICML-c3-2013-DembczynskiJKWH #approach #classification #multi #optimisation #plugin

Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization (KD, AJ, WK, WW, EH), pp. 1130–1138.

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-GeorgievN #collaboration #framework #strict

A non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines (KG, PN), pp. 1148–1156.

ICML-c3-2013-RichardBV #estimation #multi

Intersecting singularities for multi-structured estimation (ER, FRB, JPV), pp. 1157–1165.

ICML-c3-2013-DuvenaudLGTG #composition #kernel #parametricity

Structure Discovery in Nonparametric Regression through Compositional Kernel Search (DKD, JRL, RBG, JBT, ZG), pp. 1166–1174.

ICML-c3-2013-FriedlandJL #detection #social

Copy or Coincidence? A Model for Detecting Social Influence and Duplication Events (LF, DJ, ML), pp. 1175–1183.

ICML-c3-2013-GrunewalderAS

Smooth Operators (SG, AG, JST), pp. 1184–1192.

ICML-c3-2013-GoschinWL

The Cross-Entropy Method Optimizes for Quantiles (SG, AW, MLL), pp. 1193–1201.

ICML-c3-2013-DingRIS #random #topic

Topic Discovery through Data Dependent and Random Projections (WD, MHR, PI, VS), pp. 1202–1210.

ICML-c3-2013-BellemareVB #learning #recursion

Bayesian Learning of Recursively Factored Environments (MGB, JV, MB), pp. 1211–1219.

ICML-c3-2013-Agarwal #algorithm #multi #predict

Selective sampling algorithms for cost-sensitive multiclass prediction (AA), pp. 1220–1228.

ICML-c3-2013-KalaitzisLLZ

The Bigraphical Lasso (AAK, JDL, NDL, SZ), pp. 1229–1237.

ICML-c3-2013-KarninKS #multi

Almost Optimal Exploration in Multi-Armed Bandits (ZSK, TK, OS), pp. 1238–1246.

ICML-c3-2013-AndrewABL #analysis #canonical #correlation

Deep Canonical Correlation Analysis (GA, RA, JAB, KL), pp. 1247–1255.

ICML-c3-2013-DenilMF #consistency #online #random

Consistency of Online Random Forests (MD, DM, NdF), pp. 1256–1264.

ICML-c3-2013-WytockK #algorithm #energy #random #theory and practice

Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting (MW, JZK), pp. 1265–1273.

ICML-c3-2013-ChenZW #image #performance

Fast Image Tagging (MC, AXZ, KQW), pp. 1274–1282.

ICML-c3-2013-TeschSC #optimisation #probability

Expensive Function Optimization with Stochastic Binary Outcomes (MT, JGS, HC), pp. 1283–1291.

ICML-c3-2013-GerasS #multi

Multiple-source cross-validation (KG, CAS), pp. 1292–1300.

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-PascanuMB #network #on the

On the difficulty of training recurrent neural networks (RP, TM, YB), pp. 1310–1318.

ICML-c3-2013-GoodfellowWMCB #network

Maxout Networks (IJG, DWF, MM, ACC, YB), pp. 1319–1327.

ICML-c3-2013-RastegariCFHD #predict

Predictable Dual-View Hashing (MR, JC, SF, HDI, LSD), pp. 1328–1336.

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-RossD #constraints #parametricity #process

Nonparametric Mixture of Gaussian Processes with Constraints (JCR, JGD), pp. 1346–1354.

ICML-c3-2013-ReddiP #dependence #invariant #metric

Scale Invariant Conditional Dependence Measures (SJR, BP), pp. 1355–1363.

ICML-c3-2013-RossZYDB #learning #policy #predict

Learning Policies for Contextual Submodular Prediction (SR, JZ, YY, DD, DB), pp. 1364–1372.

ICML-c3-2013-KimS #approximate #modelling #topic

Manifold Preserving Hierarchical Topic Models for Quantization and Approximation (MK, PS), pp. 1373–1381.

ICML-c3-2013-OgawaST

Safe Screening of Non-Support Vectors in Pathwise SVM Computation (KO, YS, IT), pp. 1382–1390.

ICML-c3-2013-PiresSG #bound #classification #multi

Cost-sensitive Multiclass Classification Risk Bounds (BAP, CS, MG), pp. 1391–1399.

ICML-c3-2013-YiZJQJ #clustering #matrix #similarity

Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion (JY, LZ, RJ, QQ, AKJ), pp. 1400–1408.

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-Kuleshov #algorithm #analysis #component #performance

Fast algorithms for sparse principal component analysis based on Rayleigh quotient iteration (VK), pp. 1418–1425.

ICML-c3-2013-AhmedHS #documentation #modelling #process

Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document Modeling (AA, LH, AJS), pp. 1426–1434.

ICML-c3-2013-CurtinMRAGI #algorithm #independence

Tree-Independent Dual-Tree Algorithms (RRC, WBM, PR, DVA, AGG, CLI), pp. 1435–1443.

ICML-c3-2013-Romera-ParedesABP #learning #multi

Multilinear Multitask Learning (BRP, HA, NBB, MP), pp. 1444–1452.

ICML-c3-2013-JoulaniGS #feedback #learning #online

Online Learning under Delayed Feedback (PJ, AG, CS), pp. 1453–1461.

ICML-c3-2013-WangMF #adaptation #monte carlo

Adaptive Hamiltonian and Riemann Manifold Monte Carlo (ZW, SM, NdF), pp. 1462–1470.

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-HoXV #learning #on the #taxonomy

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning (JH, YX, BCV), pp. 1480–1488.

ICML-c3-2013-ToulisK #estimation

Estimation of Causal Peer Influence Effects (PT, EKK), pp. 1489–1497.