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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 5: Artificial Intelligence and Statistics, 16-18 April 2009, Hilton Clearwater Beach Resort, Clearwater Beach, Florida USA

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Editors: David van Dyk, Max Welling

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Clusterability: A Theoretical Study

; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:1-8

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Latent Force Models

Mauricio Álvarez, David Luengo, Neil D. Lawrence; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:9-16

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Variational Bridge Regression

Artin Armagan; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:17-24

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Learning Low Density Separators

Shai Ben-David, Tyler Lu, David Pal, Miroslava Sotakova; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:25-32

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Supervised Spectral Latent Variable Models

Liefeng Bo, Cristian Sminchisescu; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:33-40

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Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming

Hector Corrada Bravo, Stephen Wright, Kevin Eng, Sunduz Keles, Grace Wahba; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:41-48

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A New Perspective for Information Theoretic Feature Selection

Gavin Brown; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:49-56

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Structure Identification by Optimized Interventions

Alberto Giovanni Busetto, Joachim Buhmann; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:57-64

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Online Inference of Topics with Latent Dirichlet Allocation

Kevin Canini, Lei Shi, Thomas Griffiths; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:65-72

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Handling Sparsity via the Horseshoe

Carlos M. Carvalho, Nicholas G. Polson, James G. Scott; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:73-80

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Relational Topic Models for Document Networks

Jonathan Chang, David Blei; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:81-88

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Probabilistic Models for Incomplete Multi-dimensional Arrays

Wei Chu, Zoubin Ghahramani; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:89-96

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On Partitioning Rules for Bipartite Ranking

Stephan Clemencon, Nicolas Vayatis; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:97-104

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Gaussian Margin Machines

Koby Crammer, Mehryar Mohri, Fernando Pereira; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:105-112

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Learning Thin Junction Trees via Graph Cuts

Shahaf Dafna, Carlos Guestrin; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:113-120

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Matching Pursuit Kernel Fisher Discriminant Analysis

Tom Diethe, Zakria Hussain, David Hardoon, John Shawe-Taylor; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:121-128

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Statistical and Computational Tradeoffs in Stochastic Composite Likelihood

Joshua Dillon, Guy Lebanon; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:129-136

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Variational Inference for the Indian Buffet Process

Finale Doshi, Kurt Miller, Jurgen Van Gael, Yee Whye Teh; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:137-144

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Choosing a Variable to Clamp

Frederik Eaton, Zoubin Ghahramani; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:145-152

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The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training

Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, Pascal Vincent; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:153-160

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Semi-Supervised Affinity Propagation with Instance-Level Constraints

Inmar Givoni, Brendan Frey; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:161-168

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Multi-Manifold Semi-Supervised Learning

Andrew Goldberg, Xiaojin Zhu, Aarti Singh, Zhiting Xu, Robert Nowak; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:169-176

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Residual Splash for Optimally Parallelizing Belief Propagation

Joseph Gonzalez, Yucheng Low, Carlos Guestrin; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:177-184

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Sparse Probabilistic Principal Component Analysis

Yue Guan, Jennifer Dy; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:185-192

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Visualization Databases for the Analysis of Large Complex Datasets

Saptarshi Guha, Paul Kidwell, Ryan P. Hafen, William S. Cleveland; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:193-200

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Active Learning as Non-Convex Optimization

Andrew Guillory, Erick Chastain, Jeff Bilmes; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:201-208

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Network Completion and Survey Sampling

Steve Hanneke, Eric P. Xing; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:209-215

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Distilled sensing: selective sampling for sparse signal recovery

Jarvis Haupt, Rui Castro, Robert Nowak; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:216-223

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Infinite Hierarchical Hidden Markov Models

Katherine Heller, Yee Whye Teh, Dilan Gorur; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:224-231

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An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward

Matthew Hoffman, Nando Freitas, Arnaud Doucet, Jan Peters; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:232-239

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Maximum Entropy Density Estimation with Incomplete Presence-Only Data

Bert Huang, Ansaf Salleb-Aouissi; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:240-247

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Exploiting Probabilistic Independence for Permutations

Jonathan Huang, Carlos Guestrin, Xiaoye Jiang, Leonidas Guibas; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:248-255

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Particle Belief Propagation

Alexander Ihler, David McAllester; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:256-263

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Data Biased Robust Counter Strategies

Michael Johanson, Michael Bowling; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:264-271

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Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards

Varun Kanade, H. Brendan McMahan, Brent Bryan; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:272-279

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Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings

Minyoung Kim, Vladimir Pavlovic; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:280-287

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Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression

Nicole Kramer, Masashi Sugiyama, Mikio Braun; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:288-295

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Convex Perturbations for Scalable Semidefinite Programming

Brian Kulis, Suvrit Sra, Inderjit Dhillon; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:296-303

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Sampling Techniques for the Nystrom Method

Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:304-311

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Deep Learning using Robust Interdependent Codes

Hugo Larochelle, Dumitru Erhan, Pascal Vincent; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:312-319

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Group Nonnegative Matrix Factorization for EEG Classification

Hyekyoung Lee, Seungjin Choi; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:320-327

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Kernel Learning by Unconstrained Optimization

Fuxin Li, Yunshan Fu, Yu-Hong Dai, Cristian Sminchisescu, Jue Wang; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:328-335

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Latent Wishart Processes for Relational Kernel Learning

Wu-Jun Li, Zhihua Zhang, Dit-Yan Yeung; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:336-343

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Tighter and Convex Maximum Margin Clustering

Yu-Feng Li, Ivor W. Tsang, Jame Kwok, Zhi-Hua Zhou; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:344-351

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Learning Exercise Policies for American Options

Yuxi Li, Csaba Szepesvari, Dale Schuurmans; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:352-359

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Learning Sparse Markov Network Structure via Ensemble-of-Trees Models

Yuanqing Lin, Shenghuo Zhu, Daniel Lee, Ben Taskar; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:360-367

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A kernel method for unsupervised structured network inference

Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten Borgwardt; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:368-375

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Estimation Consistency of the Group Lasso and its Applications

Han Liu, Jian Zhang; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:376-383

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Learning a Parametric Embedding by Preserving Local Structure

Laurens van der Maaten; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:384-391

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Tractable Search for Learning Exponential Models of Rankings

Bhushan Mandhani, Marina Meila; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:392-399

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Exact and Approximate Sampling by Systematic Stochastic Search

Vikash Mansinghka, Daniel Roy, Eric Jonas, Joshua Tenenbaum; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:400-407

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Spanning Tree Approximations for Conditional Random Fields

Patrick Pletscher, Cheng Soon Ong, Joachim Buhmann; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:408-415

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Chromatic PAC-Bayes Bounds for Non-IID Data

Liva Ralaivola, Marie Szafranski, Guillaume Stempfel; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:416-423

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Inverse Optimal Heuristic Control for Imitation Learning

Nathan Ratliff, Brian Ziebart, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, Siddhartha Srinivasa; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:424-431

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Learning the Switching Rate by Discretising Bernoulli Sources Online

Steven Rooij, Tim Erven; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:432-439

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Sequential Learning of Classifiers for Structured Prediction Problems

Dan Roth, Kevin Small, Ivan Titov; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:440-447

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Deep Boltzmann Machines

Ruslan Salakhutdinov, Geoffrey Hinton; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:448-455

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Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm

Mark Schmidt, Ewout Berg, Michael Friedlander, Kevin Murphy; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:456-463

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Novelty detection: Unlabeled data definitely help

Clayton Scott, Gilles Blanchard; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:464-471

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PAC-Bayesian Generalization Bound for Density Estimation with Application to Co-clustering

Yevgeny Seldin, Naftali Tishby; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:472-479

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PAC-Bayes Analysis Of Maximum Entropy Classification

John Shawe-Taylor, David Hardoon; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:480-487

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Efficient graphlet kernels for large graph comparison

Nino Shervashidze, SVN Vishwanathan, Tobias Petri, Kurt Mehlhorn, Karsten Borgwardt; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:488-495

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Hash Kernels

Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alex Smola, Alex Strehl, S. V. N. Vishwanathan; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:496-503

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Locally Minimax Optimal Predictive Modeling with Bayesian Networks

Tomi Silander, Teemu Roos, Petri Myllymäki; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:504-511

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MCMC Methods for Bayesian Mixtures of Copulas

Ricardo Silva, Robert Gramacy; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:512-519

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Factorial Mixture of Gaussians and the Marginal Independence Model

Ricardo Silva, Zoubin Ghahramani; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:520-527

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Tractable Bayesian Inference of Time-Series Dependence Structure

Michael Siracusa, John Fisher III; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:528-535

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Relative Novelty Detection

Alex Smola, Le Song, Choon Hui Teo; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:536-543

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Tree Block Coordinate Descent for MAP in Graphical Models

David Sontag, Tommi Jaakkola; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:544-551

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The Block Diagonal Infinite Hidden Markov Model

Thomas Stepleton, Zoubin Ghahramani, Geoffrey Gordon, Tai-Sing Lee; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:552-559

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Variable Metric Stochastic Approximation Theory

Peter Sunehag, Jochen Trumpf, S.V.N. Vishwanathan, Nicol Schraudolph; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:560-566

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Variational Learning of Inducing Variables in Sparse Gaussian Processes

Michalis Titsias; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:567-574

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Non-Negative Semi-Supervised Learning

Changhu Wang, Shuicheng Yan, Lei Zhang, Hongjiang Zhang; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:575-582

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Markov Topic Models

Chong Wang, Bo Thiesson, Chris Meek, David Blei; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:583-590

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An Information Geometry Approach for Distance Metric Learning

Shijun Wang, Rong Jin; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:591-598

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Large-Margin Structured Prediction via Linear Programming

Zhuoran Wang, John Shawe-Taylor; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:599-606

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A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation

Frank Wood, Yee Whye Teh; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:607-614

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Speed and Sparsity of Regularized Boosting

Yongxin Xi, Zhen Xiang, Peter Ramadge, Robert Schapire; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:615-622

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Tree-Based Inference for Dirichlet Process Mixtures

Yang Xu, Katherine Heller, Zoubin Ghahramani; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:623-630

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Dual Temporal Difference Learning

Min Yang, Yuxi Li, Dale Schuurmans; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:631-638

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Active Sensing

Shipeng Yu, Balaji Krishnapuram, Romer Rosales, R. Bharat Rao; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:639-646

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Coherence Functions for Multicategory Margin-based Classification Methods

Zhihua Zhang, Michael Jordan, Wu-Jun Li, Dit-Yan Yeung; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:647-654

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Latent Variable Models for Dimensionality Reduction

Zhihua Zhang, Michael I. Jordan; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:655-662

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Reversible Jump MCMC for Non-Negative Matrix Factorization

Mingjun Zhong, Mark Girolami; Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, PMLR 5:663-670

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