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COLT
2000
Springer
14 years 3 months ago
Bias-Variance Error Bounds for Temporal Difference Updates
We give the first rigorous upper bounds on the error of temporal difference (td) algorithms for policy evaluation as a function of the amount of experience. These upper bounds pr...
Michael J. Kearns, Satinder P. Singh
COLT
2000
Springer
14 years 3 months ago
Improved Algorithms for Theory Revision with Queries
Judy Goldsmith, Robert H. Sloan, Balázs Sz&...
COLT
2000
Springer
14 years 3 months ago
Continuous Drifting Games
We combine the results of [13] and [8] and derive a continuous variant of a large class of drifting games. Our analysis furthers the understanding of the relationship between boos...
Yoav Freund, Manfred Opper
COLT
2000
Springer
14 years 3 months ago
Relative Expected Instantaneous Loss Bounds
Jürgen Forster, Manfred K. Warmuth
COLT
2000
Springer
14 years 3 months ago
On the Learnability and Design of Output Codes for Multiclass Problems
Output coding is a general framework for solving multiclass categorization problems. Previous research on output codes has focused on building multiclass machines given predefine...
Koby Crammer, Yoram Singer
COLT
2000
Springer
14 years 3 months ago
Logistic Regression, AdaBoost and Bregman Distances
Michael Collins, Robert E. Schapire, Yoram Singer
COLT
2000
Springer
14 years 3 months ago
Model Selection and Error Estimation
We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalizatio...
Peter L. Bartlett, Stéphane Boucheron, G&aa...
COLT
2000
Springer
14 years 3 months ago
Estimation and Approximation Bounds for Gradient-Based Reinforcement Learning
We model reinforcement learning as the problem of learning to control a Partially Observable Markov Decision Process (  ¢¡¤£¦¥§  ), and focus on gradient ascent approache...
Peter L. Bartlett, Jonathan Baxter
COLT
2000
Springer
14 years 3 months ago
The Computational Complexity of Densest Region Detection
We investigate the computational complexity of the task of detecting dense regions of an unknown distribution from un-labeled samples of this distribution. We introduce a formal l...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon