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Bylander, Tom - Department of Computer Science, University of Texas at San Antonio
QUAWDS: Diagnosis Using Different Models for Different Subtasks
Using Validation Sets to Avoid Overfitting in AdaBoost Tom Bylander and Lisa Tate
WorstCase Absolute Loss Bounds for Linear Learning Algorithms Tom Bylander
The Computational Complexity of Propositional STRIPS Planning
Worst-Case Analysis of the Perceptron and Exponentiated Update Algorithms
Predicting Financial Time Series by Genetic Programming with Trigonometric Functions and High-Order Statistics
The Binary Exponentiated Gradient Algorithm for Learning Linear Functions Tom Bylander
A PerceptronLike Online Algorithm for Tracking the Median Tom Bylander and Bruce Rosen
Learning Noisy Linear Threshold Functions Tom Bylander
A Probabilistic Analysis of Propositional STRIPS Tom Bylander
Learning Linear Threshold Approximations Using Perceptrons
The Computational Complexity of Abduction Tom Bylander, Dean Allemang,
A Linear Programming Heuristic for Optimal Planning Tom Bylander
Learning Linear Functions with Quadratic and Linear Multiplicative Tom Bylander bylander@cs.utsa.edu
