[Artificial Intelligence and Statistics Logo] Artificial Intelligence and Statistics 2001

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AISTATS 2001 Papers

Models for Conditional Probability Tables in Educational Assessment
R. G. Almond, L. DiBello, F. Jenkins, D. Senturk, R. J. Mislevy, L. S. Steinberg, D. Yan

Learning in high dimensions: modular mixture models
Hagai Attias

Learning Bayesian networks with mixed variables
Susanne Bottcher

Products of Hidden Markov Models
Andrew D. Brown, Geoffrey E. Hinton

Information-Theoretic Advisors in Invisible Chess
Ariel Bud, David Albrecht, Ann Nicholson, Ingrid Zukerman

A Non-Parametric EM-Style Algorithm for Imputing Missing Values
Rich Caruana

Managing Multiple Models
Hugh A. Chipman, Edward I. George, Robert E. McCulloch

Solving Hidden-Mode Markov Decision Problems
Samuel Ping-Man Choi, Nevin L. Zhang, Dit-Yan Yeung

Bagging and the Bayesian Bootstrap
Merlise Clyde, Herbert Lee

Hyperparameters for Soft Bayesian Model Selection
Adrian Corduneanu, Christopher M. Bishop

On searching for optimal classifiers among Bayesian networks
Robert G. Cowell

Statistical Aspects of Stochastic Logic Programs
James Cussens

Some variations on variation independence.
A. P. Dawid

Are they really neighbors? A statistical analysis of the SOM algorithm output
Eric de Bodt, Marie Cottrell, Michel Verleysen

Monte-Carlo Algorithms for the Improvement of Finite-State Stochastic Controllers: Application to Bayes-Adaptive Markov Decision Processes
Michael Duff

Why averaging classifiers can protect against overfitting
Yoav Freund, Yishay Mansour, Robert E. Schapire

Dual perturb and combine algorithm
Pierre Geurts

Handling Missing and Unreliable Information in Speech Recognition
Phil Green, Jon Barker, Martin Cooke, Ljubomir Josifovski

Discriminant Analysis on Dissimilarity Data : a New Fast Gaussian like Algorithm
Anne Guerin-Dugue, Gilles Celeux

Profile Likelihood in Directed Graphical Models from BUGS Output
Malene Hojbjerre

Is regularization unnecessary for boosting?
Wenxin Jiang

Learning mixtures of smooth, nonuniform deformation models for probabilistic image matching
Nebojsa Jojic, Patrice Simard, Brendan Frey, David Heckerman

Predicting with Variables Constructed from Temporal Sequences
Mehmet Kayaalp, Greg Cooper, Gilles Clermont

Another look at sensitivity of Bayesian networks to imprecise probabilities
Oscar Kipersztok, Haiqin Wang

Comparing Prequential Model Selection Criteria in Supervised Learning of Mixture Models
Petri Kontkanen, Petri Myllymaki, Henry Tirri

Bayesian Support Vector Regression
Martin Law, James Kwok

Variational Learning for Multi-Layer Networks of Linear Threshold Units
Neil Lawrence

On the effectiveness of the skew divergence for statistical language analysis
Lillian Lee

A Simulation Study of Three Related Causal Data Mining Algorithms
Subramani Mani, Gregory F. Cooper

Finding a path is harder than finding a tree
Christopher Meek

The Learning Curve Method Applied to Clustering
Christopher Meek, Bo Thiesson, David Heckerman

A Random Walks View of Spectral Segmentation
Marina Meila, Jianbo Shi

An improved training algorithm for kernel Fisher discriminants
Sebastian Mika, Alexander Smola, Bernhard Schoelkopf

Message Length as an Effective Ockham's Razor in Decision Tree Induction
Scott Needham, David Dowe

Using Unsupervised Learning to Guide Resampling in Imbalanced Data Sets
Adam Nickerson, Nathalie Japkowicz, Evangelos Milios

Online Bagging and Boosting
Nikunj C. Oza, Stuart Russell

Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks
J. M. Pena, I. Izarzugaza, J. A. Lozano, E. Aldasoro, P. Larranaga

Stochastic System Monitoring and Control
Gregory Provan

Can the Computer Learn to Play Music Expressively?
Christopher Raphael

On Parameter Priors for Discrete DAG Models
Dmitry Rusakov, Dan Geiger

Piecewise Linear Instrumental Variable Estimation of Causal Influence
Richard Scheines, Greg Cooper, Changwon Yoo, Tianjiao Chu

The Efficient Propagation of Arbitrary Subsets of Beliefs in Discrete-Valued Bayesian Networks
Duncan Smith

An Anytime Algorithm for Causal Inference
Peter Spirtes

Dynamic Positional Trees for Structural Image Analysis
Amos Storkey, Christopher Williams

Temporal Matching under Uncertainty
Ahmed Tawfik, Greg Scott

A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds
Michael E. Tipping, Bernhard Schoelkopf

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