AISTATS 1997

58 papers

A Bayesian Approach to CART Hugh Chipman, Edward I. George, Robert E. McCulloch

A Characterization of Bayesian Network Structures and Its Application to Leaming James I. G. Forbes

A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems Concha Bielza, Prakash P. Shenoy

A Comparison of Scientific and Engineering Criteria for Bayesian Model Selection David Heckerman, David Maxwell Chickering

A Distance Metric for Classification Trees William D. Shannon, David Banks

A Family of Algorithms for Finding Temporal Structure in Data Tim Oates, Matthew J. Schmill, David Jensen, Paul R. Cohen

A Forward Monte Carlo Method for Solving Influence Diagrams Using Local Computation John M. Charnes, Prakash P. Shenoy

A Note on Cyclic Graphs and Dynamical Feedback Systems Thomas S. Richardson, Peter Spirtes, Clark Glymour

A Polynomial Time Algorithm for Determining DAG Equivalence in the Presence of Latent Variables and Selection Bias Peter Spirtes, Thomas S. Richardson

A Variational Approach to Bayesian Logistic Regression Models and Their Extensions Tommi S. Jaakkola, Michael I. Jordan

Adjusting for Multiple Testing in Decision Tree Pruning David Jensen

An Algorithm for Bayesian Network Construction from Data Jie Cheng, David A. Bell, Weiru Liu

An Incremental Construction of a Nonparametric Regression Model Jan Smid, Petr Volf

An Objective Function for Belief Net Triangulation Marina Meilă, Michael I. Jordan

Applying a Gaussian-Bernoulli Mixture Model Network to Binary and Continuous Missing Data in Medicine David B. Rosen, Harry B. Burke

Approximate Inference and Forecast Algorithms in Graphical Models for Partially Observed Dynamic Systems Alberto Lekuona, Beatrix Lacruz, Pilar Lasala

Asessing and Improving Classification Rules David J. Hand, Kerning Yu, Niall Ada

Bayesian Information Retrieval: Preliminary Evaluation Michelle Keim, David D. Lewis, David Madigan

Bayesian Model Averaging in Rule Induction Pedro Domingos

Building an EDA Assistant: A Progress Report Robert St. Amant, Paul R. Cohen

Case-Based Probability Factoring in Bayesian Belief Networks Luigi Portinale

Combining Neural Network Regression Estimates Using Principal Components Christopher J. Merz, Michael J. Pazzani

Comparing Predictive Inference Methods for Discrete Domains Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri, Peter Grünwald

Comparing Tree-Simplification Procedures Leonard A. Breslow, David W. Aha

Conceptual Clustering with Numeric-and-Nominal Mixed Data - A New Similarity Based System Cen Li, Gautam Biswas

Cross-Validated Likelihood for Model Selection in Unsupervised Learning Padhraic Smyth

Dataset Cataloging Metadata for Machine Learning Applications Research Sally Jo Cunningham

Estimating Latent Causal Inferences: Tetrad II Model Selection and Bayesian Parameter Estimation Richard Scheines

Extensions of Undirected and Acyclic, Directed Graphical Models Thomas S. Richardson

Finding Overlapping Distributions with MML Rohan A. Baxter, Jonathan J. Oliver

Graphical Model Based Computer Adaptive Testing Russell G. Almond, Robert J. Mislevy

Heuristic Greedy Search Algorithms for Latent Variable Models Peter Spirtes, Thomas S.Richardson, Christopher Meek

How to Find Big-Oh in Your Data Set (and How Not to) C. C. McGeoch, P. R. Cohen

Inductive Inference of First-Order Models from Numeric-Symbolic Data Floriana Esposito, Sergio Caggese, Donato Malerba, Giovanni Semeraro

Inference Using Probabilistic Concept Trees Doug Fisher, Doug Talbert

Integrating Signal and Language Context to Improve Handwritten Phrase Recognition: Alternative Approaches Djamel Bouchaffra, Eugene Koontz, V. Krpasundar, Rohini K. Srihari, Sargur N. Srihari

Intelligent Assistant for Computational Scientists: Integrated Modelling, Experimentation and Analysis Dawn E. Gregory, Paul R. Cohen

Intelligent Support of Secondary Data Analysis Russell G. Almond

Leaming Influence Diagram from Data Kazuo J. Ezawa, Narendra K. Gupta

Markov Chain Monte Carlo Methods for Decision Analysis Concha Bielza, Peter Muller, David Rios Insua

Memory Based Stochastic Optimization for Validation and Tuning of Function Approximators Artur Dubrawski, Jeff Schneider

Mixed Memory Markov Models Lawrence K. Saul, Michael I. Jordan

MML Mixture Modelling of Multi-State, Poisson, vonMises Circular and Gaussian Distributions Chris S. Wallace, David L. Dowe

Multivariate Density Factorization for Independent Component Analysis: An Unsupervised Artificial Neural Network Approach Mark Girolami, Colin Fyfe

On Predictive Classification of Binary Vectors Mats Gyllenberg, Timo Koski

On the Error Probability of Model Selection for Classification Joe Suzuki

Overfitting Explained Paul R. Cohen, David Jensen

PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction Scott E. Decatur

Robust Interpretation of Neural Network Models Oma Intrator, Nathan Intrator

Robust Parameter Learning in Bayesian Networks with Missing Data Marco Ramoni, Paola Sebastiani

Statistical Aspects of Classification in Drifting Populations C. C. Taylor, G. Nakhaeizadeh, G. Kunisch

Strategies for Model Mixing in Generalized Linear Models Merlise Clyde

The Effects of Training Set Size on Decision Tree Complexity Tim Oates, David Jensen

Using Classification Trees to Improve Causal Inferences in Observational Studies Louis Anthony Cox

Using Prediction to Improve Combinatorial Optimization Search Justin A. Boyan, Andrew W. Moore

Variational Inference for Continuous Sigmoidal Bayesian Networks Brendan J. Frey

Wavelet Based Random Densities David Rios Insua, Brani Vidakovic

WWW Cache Layout to Ease Network Overload Kenichi Yoshida