AISTATS 2003

44 papers

A Bayesian Approach to Bergman’s Minimal Model Kim E. Andersen, Malene Højbjerre

A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference Pinar Muyan, Nando Freitas

A Generalized Linear Model for Principal Component Analysis of Binary Data Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar

A Unifying Theorem for Spectral Embedding and Clustering Matthew Brand, Kun Huang

An Active Approach to Collaborative Filtering Richard S. Zemel, Craig Boutilier

An Object-Oriented Bayesian Network for Estimating Mutation Rates A. Philip Dawid

Bayesian Feature Weighting for Unsupervised Learning, with Application to Object Recognition Paul Gustafson, Peter Carbonetto, Natalie Thompson, Nando Freitas

Bayesian Inference in the Presence of Determinism David Larkin, Rina Dechter

Clustering Markov States into Equivalence Classes Using SVD and Heuristic Search Algorithms Xianping Ge, Sridevi Parise, Padhraic Smyth

Combining Conjugate Direction Methods with Stochastic Approximation of Gradients Nicol N. Schraudolph, Thore Graepel

Convex Invariance Learning Tony Jebara

Curve Clustering with Random Effects Regression Mixtures Scott Gaffney, Padhraic Smyth

Data Centering in Feature Space Marina Meilă

Discriminative Model Selection for Density Models Bo Thiesson, Christopher Meek

Document Retrieval and Clustering: From Principal Component Analysis to Self-Aggregation Networks Chris Ding

Efficient Computing of Stochastic Complexity Petri Kontkanen, Wray L. Buntine, Petri Myllymäki, Jorma Rissanen, Henry Tirri

Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals Iead Rezek, Stephen J. Roberts, Peter Sykacek

Expectation Maximization of Forward Decoding Kernel Machines Shantanu Chakrabartty, Gert Cauwenberghs

Fast Forward Selection to Speed up Sparse Gaussian Process Regression Matthias W. Seeger, Christopher K. I. Williams, Neil D. Lawrence

Fast Marginal Likelihood Maximisation for Sparse Bayesian Models Michael E. Tipping, Anita C. Faul

Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs Paul Komarek, Andrew W. Moore

Generalized Belief Propagation for Approximate Inference in Hybrid Bayesian Networks Tom Heskes, Onno Zoeter

Is Multinomial PCA Multi-Faceted Clustering or Dimensionality Reduction? Wray L. Buntine, Sami Perttu

Latent Maximum Entropy Approach for Semantic $n$-Gram Language Modeling Shaojun Wang, Dale Schuurmans, Fuchun Peng

Learning Bayesian Networks from Dependency Networks: A Preliminary Study Geoff Hulten, David Maxwell Chickering, David Heckerman

Model Averaging with Bayesian Network Classifiers Denver Dash, Gregory F. Cooper

On Boosting and the Exponential Loss Abraham J. Wyner

On Improving the Efficiency of the Iterative Proportional Fitting Procedure Yee Whye Teh, Max Welling

On Retrieval Properties of Samples of Large Collections David Madigan, Yehuda Vardi, Ishay Weissman

On the Naive Bayes Model for Text Categorization Susana Eyheramendy, David D. Lewis, David Madigan

Planning by Probabilistic Inference Hagai Attias

Quick Training of Probabilistic Neural Nets by Importance Sampling Yoshua Bengio, Jean-Sébastien Senecal

Rapid Evaluation of Multiple Density Models Alexander G. Gray, Andrew W. Moore

Real-Time On-Line Learning of Transformed Hidden Markov Models from Video Nemanja Petrovic, Nebojsa Jojic, Brendan J. Frey, Thomas S. Huang

Reduced Rank Approximations of Transition Matrices Juan Lin

Refining Kernels for Regression and Uneven Classification Problems Jaz S. Kandola, John Shawe-Taylor

Sequential Importance Sampling for Visual Tracking Reconsidered Péter Torma, Csaba Szepesvári

Solving Markov Random Fields Using Semi Definite Programming Philip H. S. Torr

Structured Variational Distributions in VIBES Christopher M. Bishop, John M. Winn

Super-Resolution Enhancement of Video Christopher M. Bishop, Andrew Blake, Bhaskara Marthi

The Joint Causal Effect in Linear Structural Equation Model and Its Application to Process Analysis Manabu Kuroki, Zhihong Cai

The Sound of an Album Cover: A Probabilistic Approach to Multimedia Eric Brochu, Nando Freitas, Kejie Bao

Towards Principled Feature Selection: Relevancy, Filters and Wrappers Ioannis Tsamardinos, Constantin F. Aliferis

Tree-Reweighted Belief Propagation Algorithms and Approximate ML Estimation by Pseudo-Moment Matching Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky