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Publication search results
found 60 matches
- 1997
- Thomas S. Richardson:
Extensions of Undirected and Acyclic, Directed Graphical Models. AISTATS 1997: 407-420 - Tim Oates, David D. Jensen:
The Effects of Training Set Size on Decision Tree Complexity. AISTATS 1997: 379-390 - Thomas S. Richardson, Peter Spirtes, Clark Glymour:
A Note on Cyclic Graphs and Dynamical Feedback Systems. AISTATS 1997: 421-428 - Tim Oates, Matthew D. Schmill, David D. Jensen, Paul R. Cohen:
A Family of Algorithms for Finding Temporal Structure in Data. AISTATS 1997: 371-378 - Russell G. Almond:
Intelligent Support of Secondary Data Analysis. AISTATS 1997: 1-10 - Russell G. Almond, Robert J. Mislevy:
Graphical Model Based Computer Adaptive Testing. AISTATS 1997: 11-22 - Robert St. Amant, Paul R. Cohen:
Building an EDA Assistant: A Progress Report. AISTATS 1997: 501-512 - Rohan A. Baxter, Jonathan J. Oliver:
Finding Overlapping Distributions with MML. AISTATS 1997: 23-30 - Concha Bielza, Peter Müller, David Ríos Insua:
Markov chain Monte Carlo methods for decision analysis. AISTATS 1997: 31-38 - Concha Bielza, Prakash P. Shenoy:
A Comparison of Decision Trees, Influence Diagrams and Valuation Networks for Asymmetric Decision Problems. AISTATS 1997: 39-46 - Djamel Bouchaffra, Eugene Koontz, Venu Krpasundar, Rohini K. Srihari, Sargur N. Srihari:
Integrating Signal and Language Context to Improve Handwritten Phrase Recognition: Alternative Approaches. AISTATS 1997: 47-54 - Justin A. Boyan, Andrew W. Moore:
Using Prediction to Improve Combinatorial Optimization Search. AISTATS 1997: 55-66 - Leonard A. Breslow, David W. Aha:
Comparing Tree-Simplification Procedures. AISTATS 1997: 67-74 - John M. Charnes, Prakash P. Shenoy:
A Forward Monte Carlo Method for Solving Influence Diagrams using local Computation. AISTATS 1997: 75-82 - Jie Cheng, David A. Bell, Weiru Liu:
An Algorithm for Bayesian Network Construction from Data. AISTATS 1997: 83-90 - Hugh A. Chipman, Edward I. George, Robert E. McCulloch:
A Bayesian approach to CART. AISTATS 1997: 91-102 - Merlise A. Clyde:
Strategies for Model Mixing in Generalized Linear Models. AISTATS 1997: 103-114 - Paul R. Cohen, David D. Jensen:
Overfitting Explained. AISTATS 1997: 115-122 - Louis Anthony Cox Jr.:
Using Classification Trees to Improve Causal Inferences in Observational Studies. AISTATS 1997: 123-138 - Sally Jo Cunningham:
Dataset Cataloging Metadata for Machine Learning Applications Research. AISTATS 1997: 139-146 - Scott E. Decatur:
PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction. AISTATS 1997: 147-156 - Pedro Domingos:
Bayesian Model Averaging in Rule Induction. AISTATS 1997: 157-164 - Artur Dubrawski, Jeff Schneider:
Memory Based Stochastic Optimization for Validation and Tuning of Function Approximators. AISTATS 1997: 165-172 - Floriana Esposito, Sergio Caggese, Donato Malerba, Giovanni Semeraro:
Inductive Inference of First-Order Models from Numeric-Symbolic Data. AISTATS 1997: 173-182 - Kazuo J. Ezawa, Narendra K. Gupta:
Leaming Influence Diagram from Data. AISTATS 1997: 183-190 - Douglas H. Fisher, Douglas A. Talbert:
Inference using Probabilistic Concept Trees. AISTATS 1997: 191-202 - James I. G. Forbes:
A Characterization of Bayesian Network Structures and its Application to Leaming. AISTATS 1997: 203-210 - Brendan J. Frey:
Variational Inference for continuous Sigmoidal Bayesian Networks. AISTATS 1997: 211-222 - Mark Girolami, Colin Fyfe:
Multivariate Density Factorization for Independent Component Analysis: An Unsupervised Artificial Neural Network Approach. AISTATS 1997: 223-230 - Dawn E. Gregory, Paul R. Cohen:
Intelligent Assistant for Computational Scientists: Integrated Modelling, Experimentation and Analysis. AISTATS 1997: 231-238
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