[Artificial Intelligence and Statistics Logo] Artificial Intelligence and Statistics 1999


Program Schedule for Uncertainty 99

Tutorials: Sunday, January 3, 1999

Monday Jan 4

Tuesday Jan 5

Wednesday Jan 6

Plenary Presentations will last 25 minutes with 5 minutes for questions

Poster Sessions

Almond Herskovits Mislevey Steinberg Transfer of information between system and evidence models
Chien George Bayesian collaborative filtering
Cowell Parameter learning from incomplete data for Bayesian networks
Friedman Goldszmidt Wyner On the application of the bootstrap for computing confidence measures on features of induced Bayesian networks
Golinelli Madigan Consonni Relaxing the local independence assumption for quantitative learning in acyclic directed graphical models through hierarchical partition models
Humphreys Titterington A new method of learning in binary Boltzmann machines
Jensen Statistical Challenges to inductive inference in linked data
Jorgensen Hunt Mixture model clustering with the multimix program
Keogh Pazzani Algorithms for learning augmented bayesian classifiers
Kontkanen Myllymaki Silander Tirri Exploring the robustness of Bayesian and information-theoretic methods for predictive inference
Kreutz Reimetz Sendhoff Weihs Seelen Structure optimization of density estimation models applied to regression problems with dynamic noise
Larkin A learning rule based method of feature extraction with application to acoustic signal classification
Laskey Learning extensible multi-entity directed graphical models
Monti Cooper A latent variable model for multivariate discretization
Pearl Meshkat Testing regression models with fewer regressors
Ramoni Sebastiani Learning conditional probabilities from incomplete data: an experimental comparison
Rida Labbi Pelegrini Experts combination through density decomposition
Roedder Entropy driven probabilistic inference and inconsistency
Schmill Cohen Learned models for continuous planning
Schubert Efficient optimization of large k real-time control algorithm
Sebastiani Ramoni Model folding for data subject to nonresponse
Settimi Smith Geometry moments and Bayesian networks with hidden variables
Smyth Joint probabilistic clustering of multivariate and sequential data
Stanghellini Whittaker Analysis of multivariate time series via a hidden graphical model
Vogler Visual design support for probabilistic network application

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