MLJ 1997

40 papers

A "Microscopic" Study of Minimum Entropy Search in Learning Decomposable Markov Networks Yang Xiang, S. K. Michael Wong, Nick Cercone

A Bayesian/Information Theoretic Model of Learning to Learn via Multiple Task Sampling Jonathan Baxter

A Comparison of New and Old Algorithms for a Mixture Estimation Problem David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth

A Multistrategy Approach to Relational Knowledge Discovery in Databases Katharina Morik, Peter Brockhausen

Adaptive Probabilistic Networks with Hidden Variables John Binder, Daphne Koller, Stuart Russell, Keiji Kanazawa

An Exact Probability Metric for Decision Tree Splitting and Stopping J. Kent Martin

An Experimental and Theoretical Comparison of Model Selection Methods Michael J. Kearns, Yishay Mansour, Andrew Y. Ng, Dana Ron

Bayesian Network Classifiers Nir Friedman, Dan Geiger, Moisés Goldszmidt

Characteristic Sets for Polynomial Grammatical Inference Colin de la Higuera

CHILD: A First Step Towards Continual Learning Mark B. Ring

Clausal Discovery Luc De Raedt, Luc Dehaspe

Coping with Uncertainty in mAP Learning Kenneth Basye, Thomas L. Dean, Jeffrey Scott Vitter

Decision Tree Induction Based on Efficient Tree Restructuring Paul E. Utgoff, Neil C. Berkman, Jeffery A. Clouse

Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables David Maxwell Chickering, David Heckerman

Empirical Support for Winnow and Weighted-Majority Algorithms: Results on a Calendar Scheduling Domain Avrim Blum

Exact Learning of Formulas in Parallel Nader H. Bshouty

Exactly Learning Automata of Small Cover Time Dana Ron, Ronitt Rubinfeld

Explanation-Based Learning and Reinforcement Learning: A Unified View Thomas G. Dietterich, Nicholas S. Flann

Factorial Hidden Markov Models Zoubin Ghahramani, Michael I. Jordan

First Order Regression Aram Karalic, Ivan Bratko

Generalization of Clauses Relative to a Theory Peter Idestam-Almquist

Integrating Multiple Learning Strategies in First Order Logics Attilio Giordana, Filippo Neri, Lorenza Saitta, Marco Botta

Learning and Revising User Profiles: The Identification of Interesting Web Sites Michael J. Pazzani, Daniel Billsus

Learning and Updating of Uncertainty in Dirichlet Models Enrique F. Castillo, Ali S. Hadi, Cristina Solares

Learning Qualitative Models of Dynamic Systems David T. Hau, Enrico W. Coiera

Learning with Probabilistic Representations Pat Langley, Gregory M. Provan, Padhraic Smyth

Malicious Omissions and Errors in Answers to Membership Queries Dana Angluin, Martins Krikis, Robert H. Sloan, György Turán

Multitask Learning Rich Caruana

On the Optimality of the Simple Bayesian Classifier Under Zero-One Loss Pedro M. Domingos, Michael J. Pazzani

Online Learning Versus Offline Learning Shai Ben-David, Eyal Kushilevitz, Yishay Mansour

PAL: A Pattern-Based First-Order Inductive System Eduardo F. Morales

Predicting Nearly as Well as the Best Pruning of a Decision Tree David P. Helmbold, Robert E. Schapire

Predicting Protein Secondary Structure Using Stochastic Tree Grammars Naoki Abe, Hiroshi Mamitsuka

Pruning Algorithms for Rule Learning Johannes Fürnkranz

Representing Probabilistic Rules with Networks of Gaussian Basis Functions Volker Tresp, Jürgen Hollatz, Subutai Ahmad

Selective Sampling Using the Query by Committee Algorithm Yoav Freund, H. Sebastian Seung, Eli Shamir, Naftali Tishby

Shifting Inductive Bias with Success-Story Algorithm, Adaptive Levin Search, and Incremental Self-Improvement Jürgen Schmidhuber, Jieyu Zhao, Marco A. Wiering

The Sample Complexity of Learning Fixed-Structure Bayesian Networks Sanjoy Dasgupta

Tracking Context Changes Through Meta-Learning Gerhard Widmer

Using Background Knowledge to Build Multistrategy Learners Claude Sammut