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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
[bib][citeproc]
Clusterability: A Theoretical Study
Margareta Ackerman, Shai Ben-David;
PMLR 5:1-8
[abs][Download PDF]
Latent Force Models
Mauricio Álvarez, David Luengo, Neil D. Lawrence;
PMLR 5:9-16
[abs][Download PDF]
Variational Bridge Regression
Artin Armagan;
PMLR 5:17-24
[abs][Download PDF]
Learning Low Density Separators
Shai Ben-David, Tyler Lu, David Pal, Miroslava Sotakova;
PMLR 5:25-32
[abs][Download PDF]
Supervised Spectral Latent Variable Models
Liefeng Bo, Cristian Sminchisescu;
PMLR 5:33-40
[abs][Download PDF]
Estimating Tree-Structured Covariance Matrices via Mixed-Integer Programming
Hector Corrada Bravo, Stephen Wright, Kevin Eng, Sunduz Keles, Grace Wahba;
PMLR 5:41-48
[abs][Download PDF]
A New Perspective for Information Theoretic Feature Selection
Gavin Brown;
PMLR 5:49-56
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Structure Identification by Optimized Interventions
Alberto Giovanni Busetto, Joachim Buhmann;
PMLR 5:57-64
[abs][Download PDF]
Online Inference of Topics with Latent Dirichlet Allocation
Kevin Canini, Lei Shi, Thomas Griffiths;
PMLR 5:65-72
[abs][Download PDF]
Handling Sparsity via the Horseshoe
Carlos M. Carvalho, Nicholas G. Polson, James G. Scott;
PMLR 5:73-80
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Relational Topic Models for Document Networks
Jonathan Chang, David Blei;
PMLR 5:81-88
[abs][Download PDF]
Probabilistic Models for Incomplete Multi-dimensional Arrays
Wei Chu, Zoubin Ghahramani;
PMLR 5:89-96
[abs][Download PDF]
On Partitioning Rules for Bipartite Ranking
Stephan Clemencon, Nicolas Vayatis;
PMLR 5:97-104
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Gaussian Margin Machines
Koby Crammer, Mehryar Mohri, Fernando Pereira;
PMLR 5:105-112
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Learning Thin Junction Trees via Graph Cuts
Shahaf Dafna, Carlos Guestrin;
PMLR 5:113-120
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Matching Pursuit Kernel Fisher Discriminant Analysis
Tom Diethe, Zakria Hussain, David Hardoon, John Shawe-Taylor;
PMLR 5:121-128
[abs][Download PDF]
Statistical and Computational Tradeoffs in Stochastic Composite Likelihood
Joshua Dillon, Guy Lebanon;
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;
PMLR 5:137-144
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Choosing a Variable to Clamp
Frederik Eaton, Zoubin Ghahramani;
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;
PMLR 5:153-160
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Semi-Supervised Affinity Propagation with Instance-Level Constraints
Inmar Givoni, Brendan Frey;
PMLR 5:161-168
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Multi-Manifold Semi-Supervised Learning
Andrew Goldberg, Xiaojin Zhu, Aarti Singh, Zhiting Xu, Robert Nowak;
PMLR 5:169-176
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Residual Splash for Optimally Parallelizing Belief Propagation
Joseph Gonzalez, Yucheng Low, Carlos Guestrin;
PMLR 5:177-184
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Sparse Probabilistic Principal Component Analysis
Yue Guan, Jennifer Dy;
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;
PMLR 5:193-200
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Active Learning as Non-Convex Optimization
Andrew Guillory, Erick Chastain, Jeff Bilmes;
PMLR 5:201-208
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Network Completion and Survey Sampling
Steve Hanneke, Eric P. Xing;
PMLR 5:209-215
[abs][Download PDF]
Distilled sensing: selective sampling for sparse signal recovery
Jarvis Haupt, Rui Castro, Robert Nowak;
PMLR 5:216-223
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Infinite Hierarchical Hidden Markov Models
Katherine Heller, Yee Whye Teh, Dilan Gorur;
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;
PMLR 5:232-239
[abs][Download PDF]
Maximum Entropy Density Estimation with Incomplete Presence-Only Data
Bert Huang, Ansaf Salleb-Aouissi;
PMLR 5:240-247
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Exploiting Probabilistic Independence for Permutations
Jonathan Huang, Carlos Guestrin, Xiaoye Jiang, Leonidas Guibas;
PMLR 5:248-255
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Particle Belief Propagation
Alexander Ihler, David McAllester;
PMLR 5:256-263
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Data Biased Robust Counter Strategies
Michael Johanson, Michael Bowling;
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;
PMLR 5:272-279
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Covariance Operator Based Dimensionality Reduction with Extension to Semi-Supervised Settings
Minyoung Kim, Vladimir Pavlovic;
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;
PMLR 5:288-295
[abs][Download PDF]
Convex Perturbations for Scalable Semidefinite Programming
Brian Kulis, Suvrit Sra, Inderjit Dhillon;
PMLR 5:296-303
[abs][Download PDF]
Sampling Techniques for the Nystrom Method
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar;
PMLR 5:304-311
[abs][Download PDF]
Deep Learning using Robust Interdependent Codes
Hugo Larochelle, Dumitru Erhan, Pascal Vincent;
PMLR 5:312-319
[abs][Download PDF]
Group Nonnegative Matrix Factorization for EEG Classification
Hyekyoung Lee, Seungjin Choi;
PMLR 5:320-327
[abs][Download PDF]
Kernel Learning by Unconstrained Optimization
Fuxin Li, Yunshan Fu, Yu-Hong Dai, Cristian Sminchisescu, Jue Wang;
PMLR 5:328-335
[abs][Download PDF]
Latent Wishart Processes for Relational Kernel Learning
Wu-Jun Li, Zhihua Zhang, Dit-Yan Yeung;
PMLR 5:336-343
[abs][Download PDF]
Tighter and Convex Maximum Margin Clustering
Yu-Feng Li, Ivor W. Tsang, Jame Kwok, Zhi-Hua Zhou;
PMLR 5:344-351
[abs][Download PDF]
Learning Exercise Policies for American Options
Yuxi Li, Csaba Szepesvari, Dale Schuurmans;
PMLR 5:352-359
[abs][Download PDF]
Learning Sparse Markov Network Structure via Ensemble-of-Trees Models
Yuanqing Lin, Shenghuo Zhu, Daniel Lee, Ben Taskar;
PMLR 5:360-367
[abs][Download PDF]
A kernel method for unsupervised structured network inference
Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten Borgwardt;
PMLR 5:368-375
[abs][Download PDF]
Estimation Consistency of the Group Lasso and its Applications
Han Liu, Jian Zhang;
PMLR 5:376-383
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Learning a Parametric Embedding by Preserving Local Structure
Laurens van der Maaten;
PMLR 5:384-391
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Tractable Search for Learning Exponential Models of Rankings
Bhushan Mandhani, Marina Meila;
PMLR 5:392-399
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Exact and Approximate Sampling by Systematic Stochastic Search
Vikash Mansinghka, Daniel Roy, Eric Jonas, Joshua Tenenbaum;
PMLR 5:400-407
[abs][Download PDF]
Spanning Tree Approximations for Conditional Random Fields
Patrick Pletscher, Cheng Soon Ong, Joachim Buhmann;
PMLR 5:408-415
[abs][Download PDF]
Chromatic PAC-Bayes Bounds for Non-IID Data
Liva Ralaivola, Marie Szafranski, Guillaume Stempfel;
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;
PMLR 5:424-431
[abs][Download PDF]
Learning the Switching Rate by Discretising Bernoulli Sources Online
Steven Rooij, Tim Erven;
PMLR 5:432-439
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Sequential Learning of Classifiers for Structured Prediction Problems
Dan Roth, Kevin Small, Ivan Titov;
PMLR 5:440-447
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Deep Boltzmann Machines
Ruslan Salakhutdinov, Geoffrey Hinton;
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;
PMLR 5:456-463
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Novelty detection: Unlabeled data definitely help
Clayton Scott, Gilles Blanchard;
PMLR 5:464-471
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PAC-Bayesian Generalization Bound for Density Estimation with Application to Co-clustering
Yevgeny Seldin, Naftali Tishby;
PMLR 5:472-479
[abs][Download PDF]
PAC-Bayes Analysis Of Maximum Entropy Classification
John Shawe-Taylor, David Hardoon;
PMLR 5:480-487
[abs][Download PDF]
Efficient graphlet kernels for large graph comparison
Nino Shervashidze, SVN Vishwanathan, Tobias Petri, Kurt Mehlhorn, Karsten Borgwardt;
PMLR 5:488-495
[abs][Download PDF]
Hash Kernels
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alex Smola, Alex Strehl, S. V. N. Vishwanathan;
PMLR 5:496-503
[abs][Download PDF]
Locally Minimax Optimal Predictive Modeling with Bayesian Networks
Tomi Silander, Teemu Roos, Petri Myllymäki;
PMLR 5:504-511
[abs][Download PDF]
MCMC Methods for Bayesian Mixtures of Copulas
Ricardo Silva, Robert Gramacy;
PMLR 5:512-519
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Factorial Mixture of Gaussians and the Marginal Independence Model
Ricardo Silva, Zoubin Ghahramani;
PMLR 5:520-527
[abs][Download PDF]
Tractable Bayesian Inference of Time-Series Dependence Structure
Michael Siracusa, John Fisher III;
PMLR 5:528-535
[abs][Download PDF]
Relative Novelty Detection
Alex Smola, Le Song, Choon Hui Teo;
PMLR 5:536-543
[abs][Download PDF]
Tree Block Coordinate Descent for MAP in Graphical Models
David Sontag, Tommi Jaakkola;
PMLR 5:544-551
[abs][Download PDF]
The Block Diagonal Infinite Hidden Markov Model
Thomas Stepleton, Zoubin Ghahramani, Geoffrey Gordon, Tai-Sing Lee;
PMLR 5:552-559
[abs][Download PDF]
Variable Metric Stochastic Approximation Theory
Peter Sunehag, Jochen Trumpf, S.V.N. Vishwanathan, Nicol Schraudolph;
PMLR 5:560-566
[abs][Download PDF]
Variational Learning of Inducing Variables in Sparse Gaussian Processes
Michalis Titsias;
PMLR 5:567-574
[abs][Download PDF]
Non-Negative Semi-Supervised Learning
Changhu Wang, Shuicheng Yan, Lei Zhang, Hongjiang Zhang;
PMLR 5:575-582
[abs][Download PDF]
Markov Topic Models
Chong Wang, Bo Thiesson, Chris Meek, David Blei;
PMLR 5:583-590
[abs][Download PDF]
An Information Geometry Approach for Distance Metric Learning
Shijun Wang, Rong Jin;
PMLR 5:591-598
[abs][Download PDF]
Large-Margin Structured Prediction via Linear Programming
Zhuoran Wang, John Shawe-Taylor;
PMLR 5:599-606
[abs][Download PDF]
A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation
Frank Wood, Yee Whye Teh;
PMLR 5:607-614
[abs][Download PDF]
Speed and Sparsity of Regularized Boosting
Yongxin Xi, Zhen Xiang, Peter Ramadge, Robert Schapire;
PMLR 5:615-622
[abs][Download PDF]
Tree-Based Inference for Dirichlet Process Mixtures
Yang Xu, Katherine Heller, Zoubin Ghahramani;
PMLR 5:623-630
[abs][Download PDF]
Dual Temporal Difference Learning
Min Yang, Yuxi Li, Dale Schuurmans;
PMLR 5:631-638
[abs][Download PDF]
Active Sensing
Shipeng Yu, Balaji Krishnapuram, Romer Rosales, R. Bharat Rao;
PMLR 5:639-646
[abs][Download PDF]
Coherence Functions for Multicategory Margin-based Classification Methods
Zhihua Zhang, Michael Jordan, Wu-Jun Li, Dit-Yan Yeung;
PMLR 5:647-654
[abs][Download PDF]
Latent Variable Models for Dimensionality Reduction
Zhihua Zhang, Michael I. Jordan;
PMLR 5:655-662
[abs][Download PDF]
Reversible Jump MCMC for Non-Negative Matrix Factorization
Mingjun Zhong, Mark Girolami;
PMLR 5:663-670
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