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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