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

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@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.

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