BibSLEIGH — Proceedings of the 29th International Conference on Machine Learning

Proceedings of the 29th International Conference on Machine Learning
ICML, 2012.

KER

@proceedings{ICML-2012,
	address       = "Edinburgh, Scotland, United Kingdom",
	publisher     = "{icml.cc / Omnipress}",
	title         = "{Proceedings of the 29th International Conference on Machine Learning}",
	year          = 2012,
}

Contents (243 items)

ICML-2012-YuSL #network #speech #using: Conversational Speech Transcription Using Context-Dependent Deep Neural Networks (DY, FS, GL), p. 1.
ICML-2012-KumarTAK #data-driven #design #web: Data-driven Web Design (RK, JOT, SA, SRK), p. 2.
ICML-2012-ChambersJ #learning: Learning the Central Events and Participants in Unlabeled Text (NC, DJ), p. 3.
ICML-2012-MalisiewiczSGE #detection #image #retrieval #visual notation: Exemplar-SVMs for Visual Ob ject Detection, Label Transfer and Image Retrieval (TM, AS, AG, AAE), p. 4.
ICML-2012-BischofA #topic: Capturing topical content with frequency and exclusivity (JB, EA), p. 5.
ICML-2012-LiuW #modelling #multi #probability: TrueLabel + Confusions: A Spectrum of Probabilistic Models in Analyzing Multiple Ratings (CL, YMW), p. 6.
ICML-2012-GongZM #learning #multi #robust: Robust Multiple Manifold Structure Learning (DG, XZ, GGM), p. 7.
ICML-2012-BootsG #identification #problem: Two Manifold Problems with Applications to Nonlinear System Identification (BB, GJG), p. 8.
ICML-2012-HeKC #nearest neighbour #on the: On the Difficulty of Nearest Neighbor Search (JH, SK, SFC), p. 9.
ICML-2012-KalakrishnanRPS #learning #policy: Learning Force Control Policies for Compliant Robotic Manipulation (MK, LR, PP, SS), p. 10.
ICML-2012-SavalleRV #estimation #matrix #rank: Estimation of Simultaneously Sparse and Low Rank Matrices (PAS, ER, NV), p. 11.
ICML-2012-ShivaswamyJ #learning #online #predict: Online Structured Prediction via Coactive Learning (PS, TJ), p. 12.
ICML-2012-DhillonRFU #modelling #using #word: Using CCA to improve CCA: A new spectral method for estimating vector models of words (PSD, JR, DPF, LHU), p. 13.
ICML-2012-FoxT #bound: Bounded Planning in Passive POMDPs (RF, NT), p. 15.
ICML-2012-Ben-DavidLSS #classification #fault #using: Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss (SBD, DL, NS, KS), p. 16.
ICML-2012-Gonen #kernel #learning #multi #performance: Bayesian Efficient Multiple Kernel Learning (MG), p. 17.
ICML-2012-DundarAQR #learning #modelling #online: Bayesian Nonexhaustive Learning for Online Discovery and Modeling of Emerging Classes (MD, FA, AQ, BR), p. 18.
ICML-2012-HoiWZ #learning: Exact Soft Confidence-Weighted Learning (SCHH, JW, PZ), p. 19.
ICML-2012-ZanzottoD #distributed #kernel: Distributed Tree Kernels (FMZ, LD), p. 20.
ICML-2012-YangMJZZ #kernel #learning #multi #probability #programming: Multiple Kernel Learning from Noisy Labels by Stochastic Programming (TY, MM, RJ, LZ, YZ), p. 21.
ICML-2012-ZhangLLR #composition #rank: Improved Nystrom Low-rank Decomposition with Priors (KZ, LL, JL, AR), p. 22.
ICML-2012-CharlinZB #learning #problem: Active Learning for Matching Problems (LC, RSZ, CB), p. 23.
ICML-2012-HannahD #design #geometry #programming: Ensemble Methods for Convex Regression with Applications to Geometric Programming Based Circuit Design (LH, DBD), p. 24.
ICML-2012-LiLJX #clustering #re-engineering: Groupwise Constrained Reconstruction for Subspace Clustering (RL, BL, CJ, XX), p. 25.
ICML-2012-WangX #collaboration #matrix: Stability of matrix factorization for collaborative filtering (YXW, HX), p. 26.
ICML-2012-CrammerC #adaptation #metric #similarity: Adaptive Regularization for Similarity Measures (KC, GC), p. 27.
ICML-2012-DegrisWS #linear: Linear Off-Policy Actor-Critic (TD, MW, RSS), p. 28.
ICML-2012-KumarPK #learning #modelling #nondeterminism: Modeling Latent Variable Uncertainty for Loss-based Learning (MPK, BP, DK), p. 29.
ICML-2012-ParrishG #reduction: Dimensionality Reduction by Local Discriminative Gaussians (NP, MRG), p. 30.
ICML-2012-MnihH #image #learning #semistructured data: Learning to Label Aerial Images from Noisy Data (VM, GEH), p. 31.
ICML-2012-QuadriantoCL #clique #graph #persistent #set: The Most Persistent Soft-Clique in a Set of Sampled Graphs (NQ, CC, CHL), p. 32.
ICML-2012-BronsteinSS #learning #modelling #performance: Learning Efficient Structured Sparse Models (AMB, PS, GS), p. 33.
ICML-2012-KalyanakrishnanTAS #multi #probability #set: PAC Subset Selection in Stochastic Multi-armed Bandits (SK, AT, PA, PS), p. 34.
ICML-2012-GershmanHB #parametricity: Nonparametric variational inference (SG, MDH, DMB), p. 35.
ICML-2012-ReidWS #design #multi: The Convexity and Design of Composite Multiclass Losses (MDR, RCW, PS), p. 36.
ICML-2012-HaiderS #clustering #graph #using: Finding Botnets Using Minimal Graph Clusterings (PH, TS), p. 37.
ICML-2012-EbanBSG #learning #online #predict #sequence: Learning the Experts for Online Sequence Prediction (EE, AB, SSS, AG), p. 38.
ICML-2012-KrishnamurthyBXS #algorithm #clustering #performance: Efficient Active Algorithms for Hierarchical Clustering (AK, SB, MX, AS), p. 39.
ICML-2012-ReyR #clustering: Copula Mixture Model for Dependency-seeking Clustering (MR, VR), p. 40.
ICML-2012-BalasubramanianL #multi #predict: The Landmark Selection Method for Multiple Output Prediction (KB, GL), p. 41.
ICML-2012-KriegeM #graph #kernel: Subgraph Matching Kernels for Attributed Graphs (NK, PM), p. 42.
ICML-2012-YgerBGR #adaptation #analysis #canonical #correlation #matrix: Adaptive Canonical Correlation Analysis Based On Matrix Manifolds (FY, MB, GG, AR), p. 43.
ICML-2012-AzimiFFBH #coordination #learning: Batch Active Learning via Coordinated Matching (JA, AF, XZF, GB, BH), p. 44.
ICML-2012-AzimiJF #hybrid #optimisation: Hybrid Batch Bayesian Optimization (JA, AJ, XZF), p. 45.
ICML-2012-AvronKKS #performance #probability: Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm Regularization (HA, SK, SPK, VS), p. 46.
ICML-2012-ShanKRBSR #matrix #predict #probability #using: Gap Filling in the Plant Kingdom — Trait Prediction Using Hierarchical Probabilistic Matrix Factorization (HS, JK, PBR, AB, FS, MR), p. 47.
ICML-2012-Rakotomamonjy #infinity: Sparse Support Vector Infinite Push (AR), p. 48.
ICML-2012-GeistSLG #approach #difference #learning: A Dantzig Selector Approach to Temporal Difference Learning (MG, BS, AL, MG), p. 49.
ICML-2012-ScherrerHTH #algorithm #coordination #problem #scalability: Scaling Up Coordinate Descent Algorithms for Large ℓ1 Regularization Problems (CS, MH, AT, DH), p. 50.
ICML-2012-HanLC #learning #modelling #multi: Cross-Domain Multitask Learning with Latent Probit Models (SH, XL, LC), p. 51.
ICML-2012-LouH #learning: Structured Learning from Partial Annotations (XL, FAH), p. 52.
ICML-2012-ZhangS: Maximum Margin Output Coding (YZ, JGS), p. 53.
ICML-2012-GuL #parametricity: Sequential Nonparametric Regression (HG, JDL), p. 54.
ICML-2012-PallaKG #infinity #network: An Infinite Latent Attribute Model for Network Data (KP, DAK, ZG), p. 55.
ICML-2012-BowlingZ #on the: On Local Regret (MB, MZ), p. 56.
ICML-2012-YackleyL #learning: Smoothness and Structure Learning by Proxy (BY, TL), p. 57.
ICML-2012-MnihT #algorithm #modelling #performance #probability: A fast and simple algorithm for training neural probabilistic language models (AM, YWT), p. 58.
ICML-2012-BorboudakisT #constraints #graph #information management #network: Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral Graphs (GB, IT), p. 59.
ICML-2012-JanzaminA #composition #independence #markov: High-Dimensional Covariance Decomposition into Sparse Markov and Independence Domains (MJ, AA), p. 60.
ICML-2012-WestonWWB #collaboration #retrieval: Latent Collaborative Retrieval (JW, CW, RJW, AB), p. 61.
ICML-2012-MannorMX #nondeterminism #robust: Lightning Does Not Strike Twice: Robust MDPs with Coupled Uncertainty (SM, OM, HX), p. 62.
ICML-2012-ScholkopfJPSZM #learning #on the: On causal and anticausal learning (BS, DJ, JP, ES, KZ, JMM), p. 63.
ICML-2012-LiuWMKC: Compact Hyperplane Hashing with Bilinear Functions (WL, JW, YM, SK, SFC), p. 64.
ICML-2012-LevineK: Continuous Inverse Optimal Control with Locally Optimal Examples (SL, VK), p. 65.
ICML-2012-ZhongK #clustering #flexibility #learning #multi: Convex Multitask Learning with Flexible Task Clusters (WZ, JTYK), p. 66.
ICML-2012-WulsinJL #clustering #modelling #multi #process: A Hierarchical Dirichlet Process Model with Multiple Levels of Clustering for Human EEG Seizure Modeling (DW, SJ, BL), p. 67.
ICML-2012-WangC #process: Levy Measure Decompositions for the Beta and Gamma Processes (YW, LC), p. 68.
ICML-2012-LeRMDCCDN #learning #scalability #using: Building high-level features using large scale unsupervised learning (QVL, MR, RM, MD, GC, KC, JD, AYN), p. 69.
ICML-2012-Araya-LopezBT #using: Near-Optimal BRL using Optimistic Local Transitions (MAL, OB, VT), p. 70.
ICML-2012-TakedaMK #classification #robust: A Unified Robust Classification Model (AT, HM, TK), p. 71.
ICML-2012-DamianouETL: Manifold Relevance Determination (ACD, CHE, MKT, NDL), p. 72.
ICML-2012-KalaitzisL #analysis #component: Residual Components Analysis (AAK, NDL), p. 73.
ICML-2012-WangC12a #clustering: Clustering to Maximize the Ratio of Split to Diameter (JW, JC), p. 74.
ICML-2012-DefazioC #collaboration #performance #visual notation: A Graphical Model Formulation of Collaborative Filtering Neighbourhood Methods with Fast Maximum Entropy Training (AD, TSC), p. 75.
ICML-2012-LiH #online: On-Line Portfolio Selection with Moving Average Reversion (BL, SCHH), p. 76.
ICML-2012-Nowozin #induction: Improved Information Gain Estimates for Decision Tree Induction (SN), p. 77.
ICML-2012-Gomez-RodriguezS #network: Influence Maximization in Continuous Time Diffusion Networks (MGR, BS), p. 78.
ICML-2012-SunGS #kernel #on the #online #taxonomy: On the Size of the Online Kernel Sparsification Dictionary (YS, FJG, JS), p. 79.
ICML-2012-LozanoS #multi: Multi-level Lasso for Sparse Multi-task Regression (ACL, GS), p. 80.
ICML-2012-KimuraK #kernel #performance: Fast Computation of Subpath Kernel for Trees (DK, HK), p. 81.
ICML-2012-LinXWZ #learning: Total Variation and Euler’s Elastica for Supervised Learning (TL, HX, LW, HZ), p. 82.
ICML-2012-JalaliS #dependence #graph #learning: Learning the Dependence Graph of Time Series with Latent Factors (AJ, SS), p. 83.
ICML-2012-RavanbakhshYG #approximate #modelling #visual notation: A Generalized Loop Correction Method for Approximate Inference in Graphical Models (S(R, CNY, RG), p. 84.
ICML-2012-KolarX #consistency: Consistent Covariance Selection From Data With Missing Values (MK, EPX), p. 85.
ICML-2012-ShiSHH #question #random: Is margin preserved after random projection? (QS, CS, RH, AvdH), p. 86.
ICML-2012-ZhongG #approach #approximate #matrix: A Bayesian Approach to Approximate Joint Diagonalization of Square Matrices (MZ, MAG), p. 87.
ICML-2012-MenonJVEO #predict #ranking: Predicting accurate probabilities with a ranking loss (AKM, XJ, SV, CE, LOM), p. 88.
ICML-2012-DuanXT #adaptation #learning: Learning with Augmented Features for Heterogeneous Domain Adaptation (LD, DX, IWT), p. 89.
ICML-2012-KimKO #metric #parametricity #process #random #topic: Dirichlet Process with Mixed Random Measures: A Nonparametric Topic Model for Labeled Data (DK, SK, AHO), p. 90.
ICML-2012-MohamedHG #learning: Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning (SM, KAH, ZG), p. 91.
ICML-2012-PurushothamL #collaboration #matrix #recommendation #social #topic: Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems (SP, YL), p. 92.
ICML-2012-PletscherW: LPQP for MAP: Putting LP Solvers to Better Use (PP, SW), p. 93.
ICML-2012-YangO #clustering #composition #matrix #probability #rank: Clustering by Low-Rank Doubly Stochastic Matrix Decomposition (ZY, EO), p. 94.
ICML-2012-ChenDB #metric #modelling #normalisation #random #topic: Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling (CC, ND, WLB), p. 95.
ICML-2012-HartikainenSS #modelling #predict: State-Space Inference for Non-Linear Latent Force Models with Application to Satellite Orbit Prediction (JH, MS, SS), p. 96.
ICML-2012-BalakrishnanPL #functional #kernel: Sparse Additive Functional and Kernel CCA (SB, KP, JDL), p. 97.
ICML-2012-CotterSS #kernel #probability: The Kernelized Stochastic Batch Perceptron (AC, SSS, NS), p. 98.
ICML-2012-Busa-FeketeBK #classification #graph #performance #using: Fast classification using sparse decision DAGs (RBF, DB, BK), p. 99.
ICML-2012-KiralyT #algebra #approach #combinator #matrix #rank: A Combinatorial Algebraic Approach for the Identifiability of Low-Rank Matrix Completion (FJK, RT), p. 100.
ICML-2012-SatoN: Rethinking Collapsed Variational Bayes Inference for LDA (IS, HN), p. 101.
ICML-2012-PeharzP #learning #network: Exact Maximum Margin Structure Learning of Bayesian Networks (RP, FP), p. 102.
ICML-2012-SunRZ #adaptation #multi #named #problem: AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problem (PS, MDR, JZ), p. 103.
ICML-2012-SejdinovicGSF #kernel #testing #using: Hypothesis testing using pairwise distances and associated kernels (DS, AG, BKS, KF), p. 104.
ICML-2012-WangWHL #learning #monte carlo: Monte Carlo Bayesian Reinforcement Learning (YW, KSW, DH, WSL), p. 105.
ICML-2012-SpiliopoulouS #sequence #topic: A Topic Model for Melodic Sequences (AS, AJS), p. 106.
ICML-2012-DoppaFT #predict: Output Space Search for Structured Prediction (JRD, AF, PT), p. 107.
ICML-2012-BachrachGMG #adaptation #crowdsourcing #how #testing #visual notation: How To Grade a Test Without Knowing the Answers — A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing (YB, TG, TM, JG), p. 108.
ICML-2012-DesautelsKB #optimisation #process #trade-off: Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization (TD, AK, JWB), p. 109.
ICML-2012-JiYLJH #algorithm #bound #fault #learning: A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error Bound (MJ, TY, BL, RJ, JH), p. 110.
ICML-2012-GarnettKXSM: Bayesian Optimal Active Search and Surveying (RG, YK, XX, JGS, RPM), p. 111.
ICML-2012-PachauriCS #analysis #problem: Incorporating Domain Knowledge in Matching Problems via Harmonic Analysis (DP, MDC, VS), p. 112.
ICML-2012-ZhouLDC: Lognormal and Gamma Mixed Negative Binomial Regression (MZ, LL, DBD, LC), p. 113.
ICML-2012-Painter-WakefieldP #algorithm #learning: Greedy Algorithms for Sparse Reinforcement Learning (CPW, RP), p. 114.
ICML-2012-KolarS #estimation: Variance Function Estimation in High-dimensions (MK, JS), p. 115.
ICML-2012-XuL #multi: Conditional Sparse Coding and Grouped Multivariate Regression (MX, JDL), p. 116.
ICML-2012-MakinoT #learning #parametricity: Apprenticeship Learning for Model Parameters of Partially Observable Environments (TM, JT), p. 117.
ICML-2012-ZhaiHBW #image #modelling #process #using: Modeling Images using Transformed Indian Buffet Processes (KZ, YH, JLBG, SW), p. 118.
ICML-2012-JiangLS #3d #learning #using: Learning Object Arrangements in 3D Scenes using Human Context (YJ, ML, AS), p. 119.
ICML-2012-GuoX #classification #learning #multi: Cross Language Text Classification via Subspace Co-regularized Multi-view Learning (YG, MX), p. 120.
ICML-2012-FedorovaGNV #online #plugin #testing: Plug-in martingales for testing exchangeability on-line (VF, AJG, IN, VV), p. 121.
ICML-2012-KongD #algorithm #linear: An Iterative Locally Linear Embedding Algorithm (DK, CHQD), p. 122.
ICML-2012-BoukouvalasBC #process #using: Gaussian Process Quantile Regression using Expectation Propagation (AB, RB, DC), p. 123.
ICML-2012-KimL #graph #multi: Latent Multi-group Membership Graph Model (MK, JL), p. 124.
ICML-2012-FreitasSZ #bound #exponential #process: Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations (NdF, AJS, MZ), p. 125.
ICML-2012-MartensSS: Estimating the Hessian by Back-propagating Curvature (JM, IS, KS), p. 126.
ICML-2012-DanylukA #feature model #probability: Feature Selection via Probabilistic Outputs (APD, NA), p. 127.
ICML-2012-YueHG: Hierarchical Exploration for Accelerating Contextual Bandits (YY, SAH, CG), p. 128.
ICML-2012-VladymyrovC #algorithm #performance: Fast Training of Nonlinear Embedding Algorithms (MV, MÁCP), p. 129.
ICML-2012-KoepkeB #performance #predict: Fast Prediction of New Feature Utility (HAK, MB), p. 130.
ICML-2012-DenchevDVN #classification #optimisation #quantum #robust: Robust Classification with Adiabatic Quantum Optimization (VSD, ND, SVNV, HN), p. 131.
ICML-2012-TelgarskyD #clustering: Agglomerative Bregman Clustering (MT, SD), p. 132.
ICML-2012-StorkeyMG #machine learning: Isoelastic Agents and Wealth Updates in Machine Learning Markets (AJS, JM, KG), p. 133.
ICML-2012-HennigK: Quasi-Newton Methods: A New Direction (PH, MK), p. 134.
ICML-2012-LanctotGBB #game studies #learning: No-Regret Learning in Extensive-Form Games with Imperfect Recall (ML, RGG, NB, MB), p. 135.
ICML-2012-NiuDYS #learning #metric: Information-theoretic Semi-supervised Metric Learning via Entropy Regularization (GN, BD, MY, MS), p. 136.
ICML-2012-MahoneyDMW #approximate #matrix #performance #statistics: Fast approximation of matrix coherence and statistical leverage (MWM, PD, MMI, DPW), p. 137.
ICML-2012-XieHS #approach #automation #generative #learning: Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting (NX, HH, MS), p. 139.
ICML-2012-Memisevic #learning #multi #on the: On multi-view feature learning (RM), p. 140.
ICML-2012-HoiWZJW #algorithm #bound #kernel #learning #online #performance #scalability: Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning (SCHH, JW, PZ, RJ, PW), p. 141.
ICML-2012-Laue #algorithm #hybrid #optimisation: A Hybrid Algorithm for Convex Semidefinite Optimization (SL), p. 142.
ICML-2012-VogtR #analysis: A Complete Analysis of the l_1, p Group-Lasso (JEV, VR), p. 143.
ICML-2012-Honorio #convergence #learning #modelling #optimisation #probability: Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising Models (JH), p. 144.
ICML-2012-AvnerMS #multi: Decoupling Exploration and Exploitation in Multi-Armed Bandits (OA, SM, OS), p. 145.
ICML-2012-PrasseSLS #email #identification #learning #regular expression: Learning to Identify Regular Expressions that Describe Email Campaigns (PP, CS, NL, TS), p. 146.
ICML-2012-TangSH: Deep Mixtures of Factor Analysers (YT, RS, GEH), p. 147.
ICML-2012-KulisJ #algorithm: Revisiting k-means: New Algorithms via Bayesian Nonparametrics (BK, MIJ), p. 148.
ICML-2012-WilsonKG #network #process: Gaussian Process Regression Networks (AGW, DAK, ZG), p. 149.
ICML-2012-YuS #analysis #kernel: Analysis of Kernel Mean Matching under Covariate Shift (YY, CS), p. 150.
ICML-2012-RudermanRGP #metric #probability #strict: Tighter Variational Representations of f-Divergences via Restriction to Probability Measures (AR, MDR, DGG, JP), p. 151.
ICML-2012-DahlAL #strict #word: Training Restricted Boltzmann Machines on Word Observations (GED, RPA, HL), p. 152.
ICML-2012-ShterevD: Bayesian Watermark Attacks (IS, DBD), p. 153.
ICML-2012-Zhu #feature model #modelling #parametricity #predict: Max-Margin Nonparametric Latent Feature Models for Link Prediction (JZ), p. 154.
ICML-2012-BonillaR #learning #probability #prototype: Discriminative Probabilistic Prototype Learning (EVB, ARK), p. 155.
ICML-2012-LiuL #modelling #multi #named: Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling (YL, MTB, HL), p. 156.
ICML-2012-FujimakiH #markov #modelling: Factorized Asymptotic Bayesian Hidden Markov Models (RF, KH), p. 157.
ICML-2012-MorvantKR #bound #classification #matrix #multi: PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification (EM, SK, LR), p. 158.
ICML-2012-PlessisS #learning: Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching (MCdP, MS), p. 159.
ICML-2012-XiaoZ #problem: A Proximal-Gradient Homotopy Method for the L1-Regularized Least-Squares Problem (LX, TZ), p. 160.
ICML-2012-KarbasiIM #learning #rank: Comparison-Based Learning with Rank Nets (AK, SI, LM), p. 161.
ICML-2012-McDowellA #classification #hybrid: Semi-Supervised Collective Classification via Hybrid Label Regularization (LM, DWA), p. 162.
ICML-2012-AlamgirL #distance #graph #nearest neighbour #random: Shortest path distance in random k-nearest neighbor graphs (MA, UvL), p. 163.
ICML-2012-XiangMCCTZ #clustering #framework: A Split-Merge Framework for Comparing Clusterings (QX, QM, KMAC, HLC, IWT, ZZ), p. 164.
ICML-2012-SilverC #composition #modelling #using: Compositional Planning Using Optimal Option Models (DS, KC), p. 165.
ICML-2012-ShiS #adaptation #clustering #learning: Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation (YS, FS), p. 166.
ICML-2012-PassosRWD #flexibility #learning #modelling #multi: Flexible Modeling of Latent Task Structures in Multitask Learning (AP, PR, JW, HDI), p. 167.
ICML-2012-MerchanteGG #analysis #approach #linear #performance: An Efficient Approach to Sparse Linear Discriminant Analysis (LFSM, YG, GG), p. 168.
ICML-2012-XuWC #learning: The Greedy Miser: Learning under Test-time Budgets (ZEX, KQW, OC), p. 169.
ICML-2012-BiessmannPBH #canonical #detection #roadmap #web: Canonical Trends: Detecting Trend Setters in Web Data (FB, JMP, MLB, AH), p. 170.
ICML-2012-JoulinB #classification: A convex relaxation for weakly supervised classifiers (AJ, FRB), p. 171.
ICML-2012-DavisCBPPC #clustering #predict #relational: Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events (JD, VSC, EB, DP, PLP, MC), p. 172.
ICML-2012-KumarNKD #classification #framework #kernel #learning #multi: A Binary Classification Framework for Two-Stage Multiple Kernel Learning (AK, ANM, KK, HDI), p. 173.
ICML-2012-SohnL #invariant #learning: Learning Invariant Representations with Local Transformations (KS, HL), p. 174.
ICML-2012-DembczynskiKH #consistency #multi #ranking: Consistent Multilabel Ranking through Univariate Losses (KD, WK, EH), p. 175.
ICML-2012-BachLO #algorithm #equivalence #on the: On the Equivalence between Herding and Conditional Gradient Algorithms (FRB, SLJ, GO), p. 176.
ICML-2012-PaisleyBJ #probability: Variational Bayesian Inference with Stochastic Search (JWP, DMB, MIJ), p. 177.
ICML-2012-VaroquauxGT #clustering #correlation #design: Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering (GV, AG, BT), p. 178.
ICML-2012-ChenCK #optimisation #process: Joint Optimization and Variable Selection of High-dimensional Gaussian Processes (BC, RMC, AK), p. 179.
ICML-2012-GoodfellowCB #learning #scalability: Large-Scale Feature Learning With Spike-and-Slab Sparse Coding (IJG, ACC, YB), p. 180.
ICML-2012-MauaC: Anytime Marginal MAP Inference (DDM, CPdC), p. 181.
ICML-2012-LiuI #distributed #estimation #parametricity #pseudo: Distributed Parameter Estimation via Pseudo-likelihood (QL, ATI), p. 182.
ICML-2012-KimHS #metadata #parametricity #relational: The Nonparametric Metadata Dependent Relational Model (DIK, MCH, EBS), p. 183.
ICML-2012-TangSH12a #network: Deep Lambertian Networks (YT, RS, GEH), p. 184.
ICML-2012-NaimG #algorithm #convergence: Convergence of the EM Algorithm for Gaussian Mixtures with Unbalanced Mixing Coefficients (IN, DG), p. 185.
ICML-2012-MatuszekFZBF #learning: A Joint Model of Language and Perception for Grounded Attribute Learning (CM, NF, LSZ, LB, DF), p. 186.
ICML-2012-SilvaKB #learning: Learning Parameterized Skills (BCdS, GK, AGB), p. 187.
ICML-2012-MoldovanA #markov #process: Safe Exploration in Markov Decision Processes (TMM, PA), p. 188.
ICML-2012-PrecupB #estimation #modelling: Improved Estimation in Time Varying Models (DP, PB), p. 189.
ICML-2012-BiggioNL: Poisoning Attacks against Support Vector Machines (BB, BN, PL), p. 190.
ICML-2012-NeufeldYZKS #reduction: Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations (JN, YY, XZ, RK, DS), p. 191.
ICML-2012-McAfeeO #code generation #network #static analysis: Utilizing Static Analysis and Code Generation to Accelerate Neural Networks (LCM, KO), p. 192.
ICML-2012-BelletHS #classification #learning #linear #similarity: Similarity Learning for Provably Accurate Sparse Linear Classification (AB, AH, MS), p. 193.
ICML-2012-MysoreS #markov #modelling #performance: Variational Inference in Non-negative Factorial Hidden Markov Models for Efficient Audio Source Separation (GJM, MS), p. 194.
ICML-2012-ChenCRCC #analysis #linear: Communications Inspired Linear Discriminant Analysis (MC, WRC, MRDR, LC, ARC), p. 196.
ICML-2012-MimnoHB #probability: Sparse stochastic inference for latent Dirichlet allocation (DMM, MDH, DMB), p. 197.
ICML-2012-OuyangG #probability: Stochastic Smoothing for Nonsmooth Minimizations: Accelerating SGD by Exploiting Structure (HO, AGG), p. 198.
ICML-2012-JawanpuriaN #learning: A Convex Feature Learning Formulation for Latent Task Structure Discovery (PJ, JSN), p. 199.
ICML-2012-SamdaniR #learning #performance #predict: Efficient Decomposed Learning for Structured Prediction (RS, DR), p. 200.
ICML-2012-StulpS #adaptation #matrix #policy: Path Integral Policy Improvement with Covariance Matrix Adaptation (FS, OS), p. 201.
ICML-2012-NanCLC #optimisation: Optimizing F-measure: A Tale of Two Approaches (NY, KMAC, WSL, HLC), p. 202.
ICML-2012-YuSL12a #performance: Efficient Euclidean Projections onto the Intersection of Norm Balls (AWY, HS, FFL), p. 203.
ICML-2012-RakhlinSS #optimisation #probability: Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization (AR, OS, KS), p. 204.
ICML-2012-JalaliS12a #clustering #optimisation #using: Clustering using Max-norm Constrained Optimization (AJ, NS), p. 205.
ICML-2012-Gomez-RodriguezS12a #multi #network: Submodular Inference of Diffusion Networks from Multiple Trees (MGR, BS), p. 206.
ICML-2012-Petrik #approximate #bound #programming #robust: Approximate Dynamic Programming By Minimizing Distributionally Robust Bounds (MP), p. 207.
ICML-2012-GrunewalderLBPG #modelling: Modelling transition dynamics in MDPs with RKHS embeddings (SG, GL, LB, MP, AG), p. 208.
ICML-2012-McCartin-LimMW #approximate: Approximate Principal Direction Trees (MML, AM, RW), p. 209.
ICML-2012-BoydDPC #empirical #evaluation: Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation (KB, JD, DP, VSC), p. 210.
ICML-2012-ChenXWS #adaptation: Marginalized Denoising Autoencoders for Domain Adaptation (MC, ZEX, KQW, FS), p. 212.
ICML-2012-PoczosGS #dependence #kernel #metric: Copula-based Kernel Dependency Measures (BP, ZG, JGS), p. 213.
ICML-2012-YinCX #modelling: Group Sparse Additive Models (JY, XC, EPX), p. 214.
ICML-2012-CastroTM #policy: Policy Gradients with Variance Related Risk Criteria (DDC, AT, SM), p. 215.
ICML-2012-SchwingHPU #modelling #performance #predict #visual notation: Efficient Structured Prediction with Latent Variables for General Graphical Models (AGS, TH, MP, RU), p. 216.
ICML-2012-HazanJ #on the #random: On the Partition Function and Random Maximum A-Posteriori Perturbations (TH, TSJ), p. 217.
ICML-2012-XuYQ #composition #data analysis #infinity #modelling #multi #parametricity: Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data Analysis (ZX, FY, AQ), p. 218.
ICML-2012-SalazarC #category theory #relational: Inferring Latent Structure From Mixed Real and Categorical Relational Data (ES, LC), p. 219.
ICML-2012-BracegirdleB: Bayesian Conditional Cointegration (CB, DB), p. 220.
ICML-2012-WangB #online: Online Alternating Direction Method (HW, AB), p. 221.
ICML-2012-AzarMK #complexity #generative #learning #on the: On the Sample Complexity of Reinforcement Learning with a Generative Model (MGA, RM, BK), p. 222.
ICML-2012-ChaudhuriH #convergence #estimation #statistics: Convergence Rates for Differentially Private Statistical Estimation (KC, DH), p. 223.
ICML-2012-KumarD #learning #multi: Learning Task Grouping and Overlap in Multi-task Learning (AK, HDI), p. 224.
ICML-2012-LiuHYLW #modelling #visual notation: High Dimensional Semiparametric Gaussian Copula Graphical Models (HL, FH, MY, JDL, LAW), p. 225.
ICML-2012-ZhaiTTO: Discovering Support and Affiliated Features from Very High Dimensions (YZ, MT, IWT, YSO), p. 226.
ICML-2012-DekelTA #adaptation #learning #online #policy: Online Bandit Learning against an Adaptive Adversary: from Regret to Policy Regret (OD, AT, RA), p. 227.
ICML-2012-PiresS #estimation #learning #linear #statistics: Statistical linear estimation with penalized estimators: an application to reinforcement learning (BAP, CS), p. 228.
ICML-2012-KoS #modelling #scalability: Large Scale Variational Bayesian Inference for Structured Scale Mixture Models (YJK, MWS), p. 229.
ICML-2012-AhnBW #probability: Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring (SA, AKB, MW), p. 230.
ICML-2012-BartokZS #adaptation #algorithm #finite #monitoring #probability: An adaptive algorithm for finite stochastic partial monitoring (GB, NZ, CS), p. 231.
ICML-2012-KleinerTSJ #big data: The Big Data Bootstrap (AK, AT, PS, MIJ), p. 232.
ICML-2012-SheffetMI #behaviour #predict: Predicting Consumer Behavior in Commerce Search (OS, NM, SI), p. 233.
ICML-2012-GrunewalderLGBPP: Conditional mean embeddings as regressors (SG, GL, AG, LB, SP, MP), p. 234.
ICML-2012-RifaiDVB #generative #process: A Generative Process for Contractive Auto-Encoders (SR, YD, PV, YB), p. 235.
ICML-2012-BalleQC #learning #modelling #optimisation: Local Loss Optimization in Operator Models: A New Insight into Spectral Learning (BB, AQ, XC), p. 236.
ICML-2012-FengXY #approach #robust: Robust PCA in High-dimension: A Deterministic Approach (JF, HX, SY), p. 237.
ICML-2012-MairalY #analysis #complexity: Complexity Analysis of the Lasso Regularization Path (JM, BY), p. 238.
ICML-2012-HazanK #learning #online: Projection-free Online Learning (EH, SK), p. 239.
ICML-2012-Wagstaff #machine learning #matter: Machine Learning that Matters (KW), p. 240.
ICML-2012-FarabetCNL #learning #multi #parsing: Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers (CF, CC, LN, YL), p. 241.
ICML-2012-HazanK12a #linear: Linear Regression with Limited Observation (EH, TK), p. 242.
ICML-2012-ChenLL #algorithm #online: An Online Boosting Algorithm with Theoretical Justifications (STC, HTL, CJL), p. 243.
ICML-2012-Boulanger-LewandowskiBV #dependence #generative #modelling #music #sequence: Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription (NBL, YB, PV), p. 244.
ICML-2012-ScherrerGGG #approximate #policy: Approximate Modified Policy Iteration (BS, VG, MG, MG), p. 245.
ICML-2012-SarkarCJ #network #parametricity #predict: Nonparametric Link Prediction in Dynamic Networks (PS, DC, MIJ), p. 246.
ICML-2012-RossB #identification #learning #modelling: Agnostic System Identification for Model-Based Reinforcement Learning (SR, DB), p. 247.

Proceedings of the 29th International Conference on Machine LearningICML, 2012.

Contents (243 items)

Proceedings of the 29th International Conference on Machine Learning
ICML, 2012.