BibSLEIGH — Proceedings of the 31st International Conference on Machine Learning, Cycle 2

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

KER

@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.

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

Contents (225 items)

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