Proceedings of the 31st International Conference on Machine Learning, Cycle 1
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Proceedings of the 31st International Conference on Machine Learning, Cycle 1
ICML c1, 2014.

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@proceedings{ICML-c1-2014,
	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 1}",
	volume        = 32,
	year          = 2014,
}

Contents (85 items)

ICML-c1-2014-SamdaniCR #clustering #online
A Discriminative Latent Variable Model for Online Clustering (RS, KWC, DR), pp. 1–9.
ICML-c1-2014-MuandetFSGS #estimation #kernel
Kernel Mean Estimation and Stein Effect (KM, KF, BKS, AG, BS), pp. 10–18.
ICML-c1-2014-SteegGSD #clustering
Demystifying Information-Theoretic Clustering (GVS, AG, FS, SD), pp. 19–27.
ICML-c1-2014-ZhangHL #heuristic #performance
Covering Number for Efficient Heuristic-based POMDP Planning (ZZ, DH, WSL), pp. 28–36.
ICML-c1-2014-YangSX #classification
The Coherent Loss Function for Classification (WY, MS, HX), pp. 37–45.
ICML-c1-2014-ZhongK #multi #performance #probability
Fast Stochastic Alternating Direction Method of Multipliers (WZ, JTYK), pp. 46–54.
ICML-c1-2014-ChenSMKWK #adaptation #detection
Active Detection via Adaptive Submodularity (YC, HS, CFM, LPK, SW, AK), pp. 55–63.
ICML-c1-2014-Shalev-Shwartz0 #coordination #probability
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization (SSS, TZ), pp. 64–72.
ICML-c1-2014-LinX #adaptation #continuation #optimisation
An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization (QL, LX), pp. 73–81.
ICML-c1-2014-PinheiroC #network
Recurrent Convolutional Neural Networks for Scene Labeling (PHOP, RC), pp. 82–90.
ICML-c1-2014-MaMY #algorithm #statistics
A Statistical Perspective on Algorithmic Leveraging (PM, MWM, BY), pp. 91–99.
ICML-c1-2014-GopalanMM #online #problem
Thompson Sampling for Complex Online Problems (AG, SM, YM), pp. 100–108.
ICML-c1-2014-TaiebH #multi
Boosting multi-step autoregressive forecasts (SBT, RJH), pp. 109–117.
ICML-c1-2014-RajkumarA #algorithm #convergence #rank #statistics
A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data (AR, SA), pp. 118–126.
ICML-c1-2014-MannM #approximate #policy #scalability
Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations (TAM, SM), pp. 127–135.
ICML-c1-2014-MaillardM
Latent Bandits (OAM, SM), pp. 136–144.
ICML-c1-2014-NguyenB #performance #process
Fast Allocation of Gaussian Process Experts (TVN, EVB), pp. 145–153.
ICML-c1-2014-GopalY #clustering #modelling
Von Mises-Fisher Clustering Models (SG, YY), pp. 154–162.
ICML-c1-2014-ChazalGLM #convergence #data analysis #diagrams #estimation #persistent
Convergence rates for persistence diagram estimation in Topological Data Analysis (FC, MG, CL, BM), pp. 163–171.
ICML-c1-2014-GiesekeHOI #nearest neighbour #query
Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs (FG, JH, CEO, CI), pp. 172–180.
ICML-c1-2014-BalanCW
Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget (AKB, YC, MW), pp. 181–189.
ICML-c1-2014-TangMNMZ #analysis #comprehension #modelling #topic
Understanding the Limiting Factors of Topic Modeling via Posterior Contraction Analysis (JT, ZM, XN, QM, MZ), pp. 190–198.
ICML-c1-2014-RabinovichB #topic
The Inverse Regression Topic Model (MR, DMB), pp. 199–207.
ICML-c1-2014-ChanA #consistency #graph #modelling
A Consistent Histogram Estimator for Exchangeable Graph Models (SHC, EA), pp. 208–216.
ICML-c1-2014-LethamSS #transaction
Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data (BL, WS, AS), pp. 217–225.
ICML-c1-2014-LuoS #learning #online #towards
Towards Minimax Online Learning with Unknown Time Horizon (HL, RES), pp. 226–234.
ICML-c1-2014-MillerBAG #analysis #process
Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball (AM, LB, RPA, KG), pp. 235–243.
ICML-c1-2014-RamdasP #kernel
Margins, Kernels and Non-linear Smoothed Perceptrons (AR, JP), pp. 244–252.
ICML-c1-2014-MeiZZ #first-order #logic #modelling #robust
Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models (SM, JZ, JZ), pp. 253–261.
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-ErmonGSS #constraints #integration
Low-density Parity Constraints for Hashing-Based Discrete Integration (SE, CPG, AS, BS), pp. 271–279.
ICML-c1-2014-SeldinBCA #multi #predict
Prediction with Limited Advice and Multiarmed Bandits with Paid Observations (YS, PLB, KC, YAY), pp. 280–287.
ICML-c1-2014-NguyenPNVB #clustering #multi #parametricity
Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts (TVN, DQP, XN, SV, HB), pp. 288–296.
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-SolomonRGB #learning
Wasserstein Propagation for Semi-Supervised Learning (JS, RMR, LJG, AB), pp. 306–314.
ICML-c1-2014-ZhangZZ #infinity #markov #modelling
Max-Margin Infinite Hidden Markov Models (AZ, JZ, BZ), pp. 315–323.
ICML-c1-2014-LiuJL #approximate #kernel #performance #using
Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function (YL, SJ, SL), pp. 324–332.
ICML-c1-2014-SinghP #difference #estimation #exponential
Generalized Exponential Concentration Inequality for Renyi Divergence Estimation (SS, BP), pp. 333–341.
ICML-c1-2014-ChenLL #multi #online #problem
Boosting with Online Binary Learners for the Multiclass Bandit Problem (STC, HTL, CJL), pp. 342–350.
ICML-c1-2014-SomaKIK #algorithm #performance
Optimal Budget Allocation: Theoretical Guarantee and Efficient Algorithm (TS, NK, KI, KiK), pp. 351–359.
ICML-c1-2014-SoufianiPX #modelling #parametricity #ranking
Computing Parametric Ranking Models via Rank-Breaking (HAS, DCP, LX), pp. 360–368.
ICML-c1-2014-Abbasi-YadkoriBK
Tracking Adversarial Targets (YAY, PLB, VK), pp. 369–377.
ICML-c1-2014-ShiZ #learning #online
Online Bayesian Passive-Aggressive Learning (TS, JZ), pp. 378–386.
ICML-c1-2014-SilverLHDWR #algorithm #policy
Deterministic Policy Gradient Algorithms (DS, GL, NH, TD, DW, MAR), pp. 387–395.
ICML-c1-2014-LianREC #correlation #markov #modelling #process
Modeling Correlated Arrival Events with Latent Semi-Markov Processes (WL, VR, BE, LC), pp. 396–404.
ICML-c1-2014-BardenetDH #adaptation #approach #markov #monte carlo #scalability #towards
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach (RB, AD, CCH), pp. 405–413.
ICML-c1-2014-CicaleseLS #optimisation #testing
Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost (FC, ESL, AMS), pp. 414–422.
ICML-c1-2014-LiL #classification #multi
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification (CLL, HTL), pp. 423–431.
ICML-c1-2014-OrabonaHSJ #on the #random
On Measure Concentration of Random Maximum A-Posteriori Perturbations (FO, TH, ADS, TSJ), pp. 432–440.
ICML-c1-2014-Thomas #algorithm #bias
Bias in Natural Actor-Critic Algorithms (PT), pp. 441–448.
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-LiWLZT #dependence #modelling #on the #topic
On Modelling Non-linear Topical Dependencies (ZL, SW, JL, PZ, JT), pp. 458–466.
ICML-c1-2014-UriaML
A Deep and Tractable Density Estimator (BU, IM, HL), pp. 467–475.
ICML-c1-2014-JainT #bound #independence #learning
(Near) Dimension Independent Risk Bounds for Differentially Private Learning (PJ, AGT), pp. 476–484.
ICML-c1-2014-YangSAM #invariant #kernel #monte carlo
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels (JY, VS, HA, MWM), pp. 485–493.
ICML-c1-2014-KarampatziakisM
Discriminative Features via Generalized Eigenvectors (NK, PM), pp. 494–502.
ICML-c1-2014-LiuYF #algorithm #constraints
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint (JL, JY, RF), pp. 503–511.
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-CombesP #algorithm #bound
Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms (RC, AP), pp. 521–529.
ICML-c1-2014-IyerNS #bound #convergence #estimation #kernel
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection (AI, SN, SS), pp. 530–538.
ICML-c1-2014-KhaleghiR #consistency #estimation
Asymptotically consistent estimation of the number of change points in highly dependent time series (AK, DR), pp. 539–547.
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-Shrivastava0 #performance #permutation
Densifying One Permutation Hashing via Rotation for Fast Near Neighbor Search (AS, PL), pp. 557–565.
ICML-c1-2014-HsiehSD #divide and conquer #kernel
A Divide-and-Conquer Solver for Kernel Support Vector Machines (CJH, SS, ISD), pp. 566–574.
ICML-c1-2014-HsiehO
Nuclear Norm Minimization via Active Subspace Selection (CJH, PAO), pp. 575–583.
ICML-c1-2014-AroraBGM #bound #learning
Provable Bounds for Learning Some Deep Representations (SA, AB, RG, TM), pp. 584–592.
ICML-c1-2014-Yu0KD #learning #multi #scalability
Large-scale Multi-label Learning with Missing Labels (HFY, PJ, PK, ISD), pp. 593–601.
ICML-c1-2014-TandonR #graph #learning
Learning Graphs with a Few Hubs (RT, PDR), pp. 602–610.
ICML-c1-2014-LacosteMLL #learning
Agnostic Bayesian Learning of Ensembles (AL, MM, FL, HL), pp. 611–619.
ICML-c1-2014-AzadiS #multi #probability #towards
Towards an optimal stochastic alternating direction method of multipliers (SA, SS), pp. 620–628.
ICML-c1-2014-LanZS #monte carlo
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions (SL, BZ, BS), pp. 629–637.
ICML-c1-2014-HajiaghayiKWB #estimation #markov #performance
Efficient Continuous-Time Markov Chain Estimation (MH, BK, LW, ABC), pp. 638–646.
ICML-c1-2014-DonahueJVHZTD #named #recognition #visual notation
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition (JD, YJ, OV, JH, NZ, ET, TD), pp. 647–655.
ICML-c1-2014-YogatamaS #multi #word
Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers (DY, NAS), pp. 656–664.
ICML-c1-2014-DenilMF #random
Narrowing the Gap: Random Forests In Theory and In Practice (MD, DM, NdF), pp. 665–673.
ICML-c1-2014-ChenBSW #matrix
Coherent Matrix Completion (YC, SB, SS, RW), pp. 674–682.
ICML-c1-2014-InouyeRD #dependence #topic #word
Admixture of Poisson MRFs: A Topic Model with Word Dependencies (DI, PDR, ISD), pp. 683–691.
ICML-c1-2014-SeijenS #online
True Online TD(λ) (HvS, RSS), pp. 692–700.
ICML-c1-2014-SiHD #approximate #kernel #memory management #performance
Memory Efficient Kernel Approximation (SS, CJH, ISD), pp. 701–709.
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-Sohl-DicksteinMD #monte carlo
Hamiltonian Monte Carlo Without Detailed Balance (JSD, MM, MRD), pp. 719–726.
ICML-c1-2014-SteinhardtL
Filtering with Abstract Particles (JS, PL), pp. 727–735.
ICML-c1-2014-Suzuki #coordination #multi #probability
Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers (TS), pp. 736–744.
ICML-c1-2014-ZhouT #generative #network #predict #probability
Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction (JZ, OGT), pp. 745–753.
ICML-c1-2014-HutterHL #approach #performance
An Efficient Approach for Assessing Hyperparameter Importance (FH, HH, KLB), pp. 754–762.

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