A Bayesian Approach to Bergman’s Minimal Model

Kim E. Andersen, Malene Højbjerre; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:1-8

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Planning by Probabilistic Inference

Hagai Attias; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:9-16

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Quick Training of Probabilistic Neural Nets by Importance Sampling

Yoshua Bengio, Jean-Sébastien Senecal; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:17-24

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Super-resolution Enhancement of Video

Christopher M. Bishop, Andrew Blake, Bhaskara Marthi; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:25-32

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Structured Variational Distributions in VIBES

Christopher M. Bishop, John M. Winn; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:33-40

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A Unifying Theorem for Spectral Embedding and Clustering

Matthew Brand, Kun Huang; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:41-48

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The Sound of an Album Cover: A Probabilistic Approach to Multimedia

Eric Brochu, Nando de Freitas, Kejie Bao; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:49-56

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Is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction?

Wray L. Buntine, Sami Perttu; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:57-64

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Expectation Maximization of Forward Decoding Kernel Machines

Shantanu Chakrabartty, Gert Cauwenberghs; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:65-71

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Model Averaging with Bayesian Network Classifiers

Denver Dash, Gregory F. Cooper; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:72-79

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An object-oriented Bayesian network for estimating mutation rates

A. Philip Dawid; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:80-84

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Document Retrieval and Clustering: from Principal Component Analysis to Self-aggregation Networks

Chris Ding; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:85-92

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On the Naive Bayes Model for Text Categorization

Susana Eyheramendy, David D. Lewis, David Madigan; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:93-100

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Curve Clustering with Random Effects Regression Mixtures

Scott Gaffney, Padhraic Smyth; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:101-108

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Clustering Markov States into Equivalence Classes using SVD and Heuristic Search Algorithms

Xianping Ge, Sridevi Parise, Padhraic Smyth; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:109-116

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Rapid Evaluation of Multiple Density Models

Alexander G. Gray, Andrew W. Moore; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:117-123

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Bayesian Feature Weighting for Unsupervised Learning, with Application to Object Recognition

Paul Gustafson, Peter Carbonetto, Natalie Thompson, Nando de Freitas; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:124-131

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Generalized belief propagation for approximate inference in hybrid Bayesian networks

Tom Heskes, Onno Zoeter; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:132-140

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Learning Bayesian Networks From Dependency Networks: A Preliminary Study

Geoff Hulten, David Maxwell Chickering, David Heckerman; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:141-148

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Convex Invariance Learning

Tony Jebara; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:149-156

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Refining Kernels for Regression and Uneven Classification Problems

Jaz S. Kandola, John Shawe-Taylor; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:157-162

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Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs

Paul Komarek, Andrew W. Moore; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:163-170

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Efficient Computing of Stochastic Complexity

Petri Kontkanen, Wray L. Buntine, Petri Myllymäki, Jorma Rissanen, Henry Tirri; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:171-178

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The Joint Causal Effect in Linear Structural Equation Model and Its Application to Process Analysis

Manabu Kuroki, Zhihong Cai; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:179-186

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Bayesian Inference in the Presence of Determinism

David Larkin, Rina Dechter; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:187-194

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Reduced Rank Approximations of Transition Matrices

Juan Lin; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:195-202

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On Retrieval Properties of Samples of Large Collections

David Madigan, Yehuda Vardi, Ishay Weissman; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:203-208

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Data Centering in Feature Space

Marina Meilă; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:209-216

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A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference

Pinar Muyan, Nando de Freitas; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:217-224

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Real-time On-line Learning of Transformed Hidden Markov Models from Video

Nemanja Petrovic, Nebojsa Jojic, Brendan J. Frey, Thomas S. Huang; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:225-232

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Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals

Iead Rezek, Stephen J. Roberts, Peter Sykacek; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:233-239

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A Generalized Linear Model for Principal Component Analysis of Binary Data

Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:240-247

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Combining Conjugate Direction Methods with Stochastic Approximation of Gradients

Nicol N. Schraudolph, Thore Graepel; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:248-253

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Fast Forward Selection to Speed Up Sparse Gaussian Process Regression

Matthias W. Seeger, Christopher K. I. Williams, Neil D. Lawrence; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:254-261

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On Improving the Efficiency of the Iterative Proportional Fitting Procedure

Yee Whye Teh, Max Welling; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:262-269

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Discriminative Model Selection for Density Models

Bo Thiesson, Christopher Meek; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:270-275

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Fast Marginal Likelihood Maximisation for Sparse Bayesian Models

Michael E. Tipping, Anita C. Faul; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:276-283

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Sequential Importance Sampling for Visual Tracking Reconsidered

Péter Torma, Csaba Szepesvári; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:284-291

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Solving Markov Random Fields using Semi Definite Programming

Philip H. S. Torr; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:292-299

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Towards Principled Feature Selection: Relevancy, Filters and Wrappers

Ioannis Tsamardinos, Constantin F. Aliferis; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:300-307

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Tree-reweighted Belief Propagation Algorithms and Approximate ML Estimation by Pseudo-Moment Matching

Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:308-315

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Latent Maximum Entropy Approach for Semantic $N$-gram Language Modeling

Shaojun Wang, Dale Schuurmans, Fuchun Peng; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:316-322

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On Boosting and the Exponential Loss

Abraham J. Wyner; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:323-329

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An Active Approach to Collaborative Filtering

Richard S. Zemel, Craig Boutilier; Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:330-337

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