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Reissue R1: Sixth International Workshop on Artificial Intelligence and Statistics, 4-7 January 1997, Fort Lauderdale, FL, USA

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Editors: David Madigan, Padhraic Smyth

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Preface

David Madigan, Padhraic Smyth; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:i-xiii

Intelligent Support of Secondary Data Analysis

Russell G. Almond; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:1-10

Graphical Model Based Computer Adaptive Testing

Russell G. Almond, Robert J. Mislevy; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:11-22

Finding Overlapping Distributions with MML

Rohan A. Baxter, Jonathan J. Oliver; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:23-30

Markov chain Monte Carlo methods for decision analysis

Concha Bielza, Peter Muller, David Rios Insua; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:31-38

A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems

Concha Bielza, Prakash P.Shenoy; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:39-46

Integrating Signal and Language Context to Improve Handwritten Phrase Recognition: Alternative Approaches

Djamel Bouchaffra, Eugene Koontz, V. Krpasundar, Rohini K. Srihari, Sargur N. Srihari; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:47-54

Using Prediction to Improve Combinatorial Optimization Search

Justin A. Boyan, Andrew W. Moore; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:55-66

Comparing Tree-Simplification Procedures

Leonard A. Breslow, David W. Aha; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:67-74

A Forward Monte Carlo Method for Solving Influence Diagrams using local Computation

John M. Charnes, Prakash P. Shenoy; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:75-82

An Algorithm for Bayesian Network Construction from Data

Jie Cheng, David A. Bell, Weiru Liu; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:83-90

A Bayesian approach to CART

Hugh Chipman, Edward I. George, Robert E. McCulloch; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:91-102

Strategies for Model Mixing in Generalized Linear Models

Merlise Clyde; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:103-114

Overfitting Explained

Paul R. Cohen, David Jensen; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:115-122

Using Classification Trees to Improve Causal Inferences in Observational Studies

Louis Anthony Cox Jr; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:123-138

Dataset Cataloging Metadata for Machine Learning Applications Research

Sally Jo Cunningham; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:139-146

PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction

Scott E. Decatur; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:147-156

Bayesian Model Averaging in Rule Induction

Pedro Domingos; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:157-164

Memory Based Stochastic Optimization for Validation and Tuning of Function Approximators

Artur Dubrawski, Jeff Schneider; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:165-172

Inductive Inference of First-Order Models from Numeric-Symbolic Data

Floriana Esposito, Sergio Caggese, Donato Malerba, Giovanni Semeraro; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:173-182

Leaming Influence Diagram from Data

Kazuo J. Ezawa, Narendra K. Gupta; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:183-190

Inference using Probabilistic Concept Trees

Doug Fisher, Doug Talbert; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:191-202

A Characterization of Bayesian Network Structures and its Application to Leaming

James I. G. Forbes; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:203-210

Variational Inference for continuous Sigmoidal Bayesian Networks

Brendan J. Frey; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:211-222

Multivariate Density Factorization for Independent Component Analysis: An Unsupervised Artificial Neural Network Approach

Mark Girolami, Colin Fyfe; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:223-230

Intelligent Assistant for Computational Scientists: Integrated Modelling, Experimentation and Analysis

Dawn E. Gregory, Paul R. Cohen; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:231-238

On Predictive Classification of Binary Vectors

Mats Gyllenberg, Timo Koski; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:239-242

Asessing and Improving Classification Rules

David J. Hand, Kerning Yu, Niall Ada; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:243-254

Robust Interpretation of Neural Network models

Oma Intrator, Nathan Intrator; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:255-262

Wavelet based Random Densities

David Rios Insua, Brani Vidakovic; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:263-274

A Comparison of Scientific and Engineering Criteria for Bayesian Model Selection

David Heckerman, David Maxwell Chickering; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:275-282

A Variational Approach to Bayesian Logistic Regression Models and their Extensions

Tommi S. Jaakkola, Michael I. Jordan; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:283-294

Adjusting for Multiple Testing in Decision Tree Pruning

David Jensen; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:295-302

Bayesian Information Retrieval: Preliminary Evaluation

Michelle Keim, David D. Lewis, David Madigan; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:303-318

Comparing Predictive Inference Methods for Discrete Domains

Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:311-318

Approximate Inference and Forecast Algorithms in Graphical Models for Partially Observed Dynamic Systems

Alberto Lekuona, Beatrix Lacruz, Pilar Lasala; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:319-319

Conceptual Clustering with Numeric-and-Nominal Mixed Data - A New Similarity Based System

Cen Li, Gautam Biswas; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:327-346

How to Find Big-Oh in Your Data Set (and How Not To)

C. C. McGeoch, P. R. Cohen; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:347-354

An Objective Function for Belief Net Triangulation

Marina Meilă, Michael I. Jordan; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:355-362

Combining Neural Network Regression Estimates Using Principal Components

Christopher J. Merz, Michael J. Pazzani; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:363-370

A Family of Algorithms for Finding Temporal Structure in Data

Tim Oates, Matthew J. Schmill, David Jensen, Paul R. Cohen; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:371-378

The Effects of Training Set Size on Decision Tree Complexity

Tim Oates, David Jensen; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:379-390

Case-based Probability Factoring in Bayesian Belief Networks

Luigi Portinale; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:391-398

Robust Parameter Learning in Bayesian Networks with Missing Data

Marco Ramoni, Paola Sebastiani; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:399-406

Extensions of Undirected and Acyclic, Directed Graphical Models

Thomas S. Richardson; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:407-420

A Note on Cyclic Graphs and Dynamical Feedback Systems

Thomas S. Richardson, Peter Spirtes, Clark Glymour; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:421-428

Applying a Gaussian-Bernoulli Mixture Model Network to Binary and Continuous Missing Data in Medicine

David B. Rosen, Harry B. Burke; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:429-436

Mixed Memory Markov Models

Lawrence K. Saul, Michael I. Jordan; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:437-444

Estimating Latent Causal Inferences: Tetrad II model selection and Bayesian parameter estimation

Richard Scheines; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:445-456

A Distance Metric for Classification Trees

William D. Shannon, David Banks; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:457-464

An Incremental Construction of a Nonparametric Regression Model

Jan Smid, Petr Volf; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:465-472

Cross-validated Likelihood for Model Selection in Unsupervised Learning

Padhraic Smyth; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:473-480

Heuristic Greedy Search Algorithms for Latent Variable Models

Peter Spirtes, Thomas S.Richardson, Christopher Meek; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:481-488

A Polynomial Time Algorithm for Determining DAG Equivalence in the Presence of Latent Variables and Selection Bias

Peter Spirtes, Thomas S. Richardson; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:489-500

Building an EDA Assistant: A Progress Report

Robert St. Amant, Paul R. Cohen; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:501-512

On the Error Probability of Model Selection for Classification

Joe Suzuki; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:513-520

Statistical Aspects of Classification in Drifting Populations

C. C. Taylor, G. Nakhaeizadeh, G. Kunisch; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:521-528

MML Mixture Modelling of Multi-state, Poisson, vonMises circular and Gaussian Distributions

Chris S. Wallace, David L. Dowe; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:529-536

WWW Cache Layout to Ease Network Overload

Kenichi Yoshida; Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, PMLR R1:537-548

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