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9th AISTATS 2003: Key West, Florida, USA
- Christopher M. Bishop, Brendan J. Frey:
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, AISTATS 2003, Key West, Florida, USA, January 3-6, 2003. Society for Artificial Intelligence and Statistics 2003, ISBN 0-9727358-0-1 - Michael E. Tipping, Anita C. Faul:
Fast Marginal Likelihood Maximisation for Sparse Bayesian Models. 276-283 - Nicol N. Schraudolph, Thore Graepel:
Combining Conjugate Direction Methods with Stochastic Approximation of Gradients. 248-253 - Shantanu Chakrabartty, Gert Cauwenberghs:
Expectation Maximization of Forward Decoding Kernel Machines. 65-71 - Tom Heskes, Onno Zoeter:
Generalized belief propagation for approximate inference in hybrid Bayesian networks. 132-140 - Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky:
Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matching. 308-315 - Denver Dash, Gregory F. Cooper:
Model Averaging with Bayesian Network Classifiers. 72-79 - Matthias W. Seeger, Christopher K. I. Williams, Neil D. Lawrence:
Fast Forward Selection to Speed Up Sparse Gaussian Process Regression. 254-261 - Yee Whye Teh, Max Welling:
On Improving the Efficiency of the Iterative Proportional Fitting Procedure. 262-269 - Alexander G. Gray, Andrew W. Moore:
Rapid Evaluation of Multiple Density Models. 117-123 - Kim E. Andersen, Malene Højbjerre:
A Bayesian Approach to Bergman's Minimal Model. 1-8 - David Larkin, Rina Dechter:
Bayesian Inference in the Presence of Determinism. 187-194 - Tony Jebara:
Convex Invariance Learning. 149-156 - Abraham J. Wyner:
On Boosting and the Exponential Loss. 323-329 - Philip H. S. Torr:
Solving Markov Random Fields using Semi Definite Programming. 292-299 - Eric Brochu, Nando de Freitas, Kejie Bao:
The Sound of an Album Cover: A Probabilistic Approach to Multimedia. 49-56 - Andrew I. Schein, Lawrence K. Saul, Lyle H. Ungar:
A Generalized Linear Model for Principal Component Analysis of Binary Data. 240-247 - Jaz S. Kandola, John Shawe-Taylor:
Refining Kernels for Regression and Uneven Classification Problems. 157-162 - Marina Meila:
Data centering in feature space. 209-216 - Geoff Hulten, David Maxwell Chickering, David Heckerman:
Learning Bayesian Networks From Dependency Networks: A Preliminary Study. 141-148 - Ioannis Tsamardinos, Constantin F. Aliferis:
Towards Principled Feature Selection: Relevancy, Filters and Wrappers. 300-307 - Manabu Kuroki, Zhihong Cai:
The Joint Causal Effect in Linear Structural Equation Model and Its Application to Process Analysis. 179-186 - Chris Ding:
Document Retrieval and Clustering: from Principal Component Analysis to Self-aggregation Networks. 85-92 - Christopher M. Bishop, John M. Winn:
Structured Variational Distributions in VIBES. 33-40 - Juan Lin:
Reduced Rank Approximations of Transition Matrices. 195-202 - Iead Rezek, Stephen J. Roberts, Peter Sykacek:
Ensemble Coupled Hidden Markov Models for Joint Characterisation of Dynamic Signals. 233-239 - Xianping Ge, Sridevi Parise, Padhraic Smyth:
Clustering Markov States into Equivalence Classes using SVD and Heuristic Search Algorithms. 109-116 - Yoshua Bengio, Jean-Sébastien Senecal:
Quick Training of Probabilistic Neural Nets by Importance Sampling. 17-24 - Susana Eyheramendy, David D. Lewis, David Madigan:
On the Naive Bayes Model for Text Categorization. 93-100 - Paul Gustafson, Peter Carbonetto, Natalie Thompson, Nando de Freitas:
Bayesian Feature Weighting for Unsupervised Learning, with Application to Object Recognition. 124-131 - Pinar Muyan, Nando de Freitas:
A Blessing of Dimensionality: Measure Concentration and Probabilistic Inference. 217-224 - Shaojun Wang, Dale Schuurmans, Fuchun Peng:
Latent Maximum Entropy Approach for Semantic N-gram Language Modeling. 316-322 - Richard S. Zemel, Craig Boutilier:
An Active Approach to Collaborative Filtering. 330-337 - Petri Kontkanen, Wray L. Buntine, Petri Myllymäki, Jorma Rissanen, Henry Tirri:
Efficient Computing of Stochastic Complexity. 171-178 - Paul Komarek, Andrew W. Moore:
Fast Robust Logistic Regression for Large Sparse Datasets with Binary Outputs. 163-170 - Scott Gaffney, Padhraic Smyth:
Curve Clustering with Random Effects Regression Mixtures. 101-108 - Nemanja Petrovic, Nebojsa Jojic, Brendan J. Frey, Thomas S. Huang:
Real-time On-line Learning of Transformed Hidden Markov Models from Video. 225-232 - A. Philip Dawid:
An object-oriented Bayesian network for estimating mutation rates. 80-84 - Matthew Brand, Kun Huang:
A unifying theorem for spectral embedding and clustering. 41-48 - David Madigan, Yehuda Vardi, Ishay Weissman:
On Retrieval Properties of Samples of Large Collections. 203-208 - Péter Torma, Csaba Szepesvári:
Sequential Importance Sampling for Visual Tracking Reconsidered. 284-291 - Christopher M. Bishop, Andrew Blake, Bhaskara Marthi:
Super-resolution Enhancement of Video. 25-32 - Bo Thiesson, Christopher Meek:
Discriminative Model Selection for Density Models. 270-275 - Hagai Attias:
Planning by Probabilistic Inference. 9-16 - Wray L. Buntine, Sami Perttu:
Is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction? 57-64
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