MLJ 1999

42 papers

A Dichotomy Theorem for Learning Quantified Boolean Formulas Víctor Dalmau

A Principal Components Approach to Combining Regression Estimates Christopher J. Merz, Michael J. Pazzani

A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geometric Patterns Sally A. Goldman, Stephen D. Scott

A Winnow-Based Approach to Context-Sensitive Spelling Correction Andrew R. Golding, Dan Roth

An Algorithm That Learns What's in a Name Daniel M. Bikel, Richard M. Schwartz, Ralph M. Weischedel

An Efficient Extension to Mixture Techniques for Prediction and Decision Trees Fernando C. N. Pereira, Yoram Singer

An Efficient Method to Estimate Bagging's Generalization Error David H. Wolpert, William G. Macready

An Efficient, Probabilistically Sound Algorithm for Segmentation and Word Discovery Michael R. Brent

An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants Eric Bauer, Ron Kohavi

An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition Geoffrey I. Webb, Jason Wells, Zijian Zheng

An Introduction to Variational Methods for Graphical Models Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola, Lawrence K. Saul

Concept Learning and Feature Selection Based on Square-Error Clustering Boris G. Mirkin

Derandomizing Stochastic Prediction Strategies V. G. Vovk

Effective and Efficient Knowledge Base Refinement Leonardo Carbonara, Derek H. Sleeman

Efficient Read-Restricted Monotone CNF/DNF Dualization by Learning with Membership Queries Carlos Domingo, Nina Mishra, Leonard Pitt

Estimation of Time-Varying Parameters in Statistical Models: An Optimization Approach Dimitris Bertsimas, David Gamarnik, John N. Tsitsiklis

Exploration of Multi-State Environments: Local Measures and Back-Propagation of Uncertainty Nicolas Meuleau, Paul Bourgine

Forgetting Exceptions Is Harmful in Language Learning Walter Daelemans, Antal van den Bosch, Jakub Zavrel

General and Efficient Multisplitting of Numerical Attributes Tapio Elomaa, Juho Rousu

Improved Boosting Algorithms Using Confidence-Rated Predictions Robert E. Schapire, Yoram Singer

Introducing the Special Issue of Machine Learning Selected from Papers Presented at the 1997 Conference on Computational Learning Theory, COLT'97 John Shawe-Taylor

Large Margin Classification Using the Perceptron Algorithm Yoav Freund, Robert E. Schapire

Learning Function-Free Horn Expressions Roni Khardon

Learning Information Extraction Rules for Semi-Structured and Free Text Stephen Soderland

Learning to Parse Natural Language with Maximum Entropy Models Adwait Ratnaparkhi

Learning to Reason with a Restricted View Roni Khardon, Dan Roth

Learning to Take Actions Roni Khardon

Linearly Combining Density Estimators via Stacking Padhraic Smyth, David H. Wolpert

Minimum Generalization via Reflection: A Fast Linear Threshold Learner Steven Hampson, Dennis F. Kibler

Mixed Memory Markov Models: Decomposing Complex Stochastic Processes as Mixtures of Simpler Ones Lawrence K. Saul, Michael I. Jordan

On the Sample Complexity for Nonoverlapping Neural Networks Michael Schmitt

Pasting Small Votes for Classification in Large Databases and On-Line Leo Breiman

Projection Learning Leslie G. Valiant

Similarity-Based Models of Word Cooccurrence Probabilities Ido Dagan, Lillian Lee, Fernando C. N. Pereira

Some PAC-Bayesian Theorems David A. McAllester

Statistical Models for Text Segmentation Doug Beeferman, Adam L. Berger, John D. Lafferty

Structural Results About On-Line Learning Models with and Without Queries Peter Auer, Philip M. Long

The Complexity of Learning According to Two Models of a Drifting Environment Philip M. Long

Toward a Model of Intelligence as an Economy of Agents Eric B. Baum

Universal Portfolios with and Without Transaction Costs Avrim Blum, Adam Kalai

Using Correspondence Analysis to Combine Classifiers Christopher J. Merz

Using Decision Trees to Construct a Practical Parser Masahiko Haruno, Satoshi Shirai, Yoshifumi Ooyama