papers.html

---
layout: default
title: Papers
---

<h2>AISTATS 2001 Papers</h2>

<a href="files/almond146.ps"><it>Models for Conditional Probability Tables in Educational Assessment</it></a>
<br>R. G. Almond, L. DiBello, F. Jenkins, D. Senturk, R. J. Mislevy, L. S. Steinberg, D. Yan<br><p>
<a href="files/attias182.ps"><it>Learning in high dimensions: modular mixture models</it></a>
<br>Hagai Attias<br><p>
<a href="files/bottcher150.ps"><it>Learning Bayesian networks with mixed variables</it></a>
<br>Susanne Bottcher<br><p>
<a href="files/brown143.ps"><it>Products of Hidden Markov Models</it></a>
<br>Andrew D. Brown, Geoffrey E. Hinton<br><p>
<a href="files/bud159.ps"><it>Information-Theoretic Advisors in Invisible Chess</it></a>
<br>Ariel Bud, David Albrecht, Ann Nicholson, Ingrid Zukerman<br><p>
<a href="files/caruana162.ps"><it>A Non-Parametric EM-Style Algorithm for Imputing Missing Values</it></a>
<br>Rich Caruana<br><p>
<a href="files/chipman148.ps"><it>Managing Multiple Models</it></a>
<br>Hugh A. Chipman, Edward I. George, Robert E. McCulloch<br><p>
<a href="files/choi132.ps"><it>Solving Hidden-Mode Markov Decision Problems</it></a>
<br>Samuel Ping-Man Choi, Nevin L. Zhang, Dit-Yan Yeung<br><p>
<a href="files/clyde129.ps"><it>Bagging and the Bayesian Bootstrap</it></a>
<br>Merlise Clyde, Herbert Lee<br><p>
<a href="files/corduneanu151.ps"><it>Hyperparameters for Soft Bayesian Model Selection</it></a>
<br>Adrian Corduneanu, Christopher M. Bishop<br><p>
<a href="files/cowell181.ps"><it>On searching for optimal classifiers among Bayesian networks</it></a>
<br>Robert G. Cowell<br><p>
<a href="files/cussens138.ps"><it>Statistical Aspects of Stochastic Logic Programs</it></a>
<br>James Cussens<br><p>
<a href="files/dawid178.ps"><it>Some variations on variation independence.</it></a>
<br>A. P. Dawid<br><p>
<a href="files/debodt105.pdf"><it>Are they really neighbors? A statistical analysis of the SOM algorithm output</it></a>
<br>Eric de Bodt, Marie Cottrell, Michel Verleysen<br><p>
<a href="files/duff135.ps"><it>Monte-Carlo Algorithms for the Improvement of Finite-State Stochastic Controllers: Application to Bayes-Adaptive Markov Decision Processes</it></a>
<br>Michael Duff<br><p>
<a href="files/freund154.ps"><it>Why averaging classifiers can protect against overfitting</it></a>
<br>Yoav Freund, Yishay Mansour, Robert E. Schapire<br><p>
<a href="files/geurts123.ps"><it>Dual perturb and combine algorithm</it></a>
<br>Pierre Geurts<br><p>
<a href="files/green126.pdf"><it>Handling Missing and Unreliable Information in Speech Recognition</it></a>
<br>Phil Green, Jon Barker, Martin Cooke, Ljubomir Josifovski<br><p>
<a href="files/guerin-dugue108.ps"><it>Discriminant Analysis on Dissimilarity Data : a New Fast Gaussian like Algorithm</it></a>
<br>Anne Guerin-Dugue, Gilles Celeux<br><p>
<a href="files/hojbjerre113.ps"><it>Profile Likelihood in Directed Graphical Models from BUGS Output</it></a>
<br>Malene Hojbjerre<br><p>
<a href="files/jiang110.ps"><it>Is regularization unnecessary for boosting?</it></a>
<br>Wenxin Jiang<br><p>
<a href="files/jojic186.ps"><it>Learning mixtures of smooth, nonuniform deformation models for probabilistic image matching</it></a>
<br>Nebojsa Jojic, Patrice Simard, Brendan Frey, David Heckerman<br><p>
<a href="files/kayaalp179.pdf"><it>Predicting with Variables Constructed from Temporal Sequences</it></a>
<br>Mehmet Kayaalp, Greg Cooper, Gilles Clermont<br><p>
<a href="files/kipersztok176.pdf"><it>Another look at sensitivity of Bayesian networks to imprecise probabilities</it></a>
<br>Oscar Kipersztok, Haiqin Wang<br><p>
<a href="files/kontkanen136.ps"><it>Comparing Prequential Model Selection Criteria in Supervised Learning of Mixture Models</it></a>
<br>Petri Kontkanen, Petri Myllymaki, Henry Tirri<br><p>
<a href="files/law119.ps"><it>Bayesian Support Vector Regression</it></a>
<br>Martin Law, James Kwok<br><p>
<a href="files/lawrence141.pdf"><it>Variational Learning for Multi-Layer Networks of Linear Threshold Units</it></a>
<br>Neil Lawrence<br><p>
<a href="files/lee118.pdf"><it>On the effectiveness of the skew divergence for statistical language analysis</it></a>
<br>Lillian Lee<br><p>
<a href="files/mani131.pdf"><it>A Simulation Study of Three Related Causal Data Mining Algorithms</it></a>
<br>Subramani Mani, Gregory F. Cooper<br><p>
<a href="files/meek153.ps"><it>Finding a path is harder than finding a tree</it></a>
<br>Christopher Meek<br><p>
<a href="files/meek158.ps"><it>The Learning Curve Method Applied to Clustering</it></a>
<br>Christopher Meek, Bo Thiesson, David Heckerman<br><p>
<a href="files/meila177.ps"><it>A Random Walks View of Spectral Segmentation</it></a>
<br>Marina Meila, Jianbo Shi<br><p>
<a href="files/mika187.pdf"><it>An improved training algorithm for kernel Fisher discriminants</it></a>
<br>Sebastian Mika, Alexander Smola, Bernhard Schoelkopf<br><p>
<a href="files/needham122.ps"><it>Message Length as an Effective Ockham's Razor in Decision Tree Induction</it></a>
<br>Scott Needham, David Dowe<br><p>
<a href="files/nickerson155.ps"><it>Using Unsupervised Learning to Guide Resampling in Imbalanced Data Sets</it></a>
<br>Adam Nickerson, Nathalie Japkowicz, Evangelos Milios<br><p>
<a href="files/oza149.ps"><it>Online Bagging and Boosting</it></a>
<br>Nikunj C. Oza, Stuart Russell<br><p>
<a href="files/pena183.pdf"><it>Geographical clustering of cancer incidence by means of Bayesian networks and conditional Gaussian networks</it></a>
<br>J. M. Pena, I. Izarzugaza, J. A. Lozano, E. Aldasoro, P. Larranaga<br><p>
<a href="files/provan128.pdf"><it>Stochastic System Monitoring and Control</it></a>
<br>Gregory Provan<br><p>
<a href="files/raphael114.ps"><it>Can the Computer Learn to Play Music Expressively?</it></a>
<br>Christopher Raphael<br><p>
<a href="files/rusakov167.ps"><it>On Parameter Priors for Discrete DAG Models</it></a>
<br>Dmitry Rusakov, Dan Geiger<br><p>
<a href="files/scheines164.ps"><it>Piecewise Linear Instrumental Variable Estimation of Causal Influence</it></a>
<br>Richard Scheines, Greg Cooper, Changwon Yoo, Tianjiao Chu<br><p>
<a href="files/smith175.ps"><it>The Efficient Propagation of Arbitrary Subsets of Beliefs in Discrete-Valued Bayesian Networks</it></a>
<br>Duncan Smith<br><p>
<a href="files/spirtes156.ps"><it>An Anytime Algorithm for Causal Inference</it></a>
<br>Peter Spirtes<br><p>
<a href="files/storkey109.ps"><it>Dynamic Positional Trees for Structural Image Analysis</it></a>
<br>Amos Storkey, Christopher Williams<br><p>
<a href="files/tawfik147.ps"><it>Temporal Matching under Uncertainty</it></a>
<br>Ahmed Tawfik, Greg Scott<br><p>
<a href="files/tipping140.pdf"><it>A Kernel Approach for Vector Quantization with Guaranteed Distortion Bounds</it></a>
<br>Michael E. Tipping, Bernhard Schoelkopf<br><p>