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» Improved bounds on the sample complexity of learning
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NIPS
1998
13 years 9 months ago
Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms
In this paper, we address two issues of long-standing interest in the reinforcement learning literature. First, what kinds of performance guarantees can be made for Q-learning aft...
Michael J. Kearns, Satinder P. Singh
COLT
2001
Springer
14 years 1 days ago
Smooth Boosting and Learning with Malicious Noise
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
Rocco A. Servedio
ALT
2006
Springer
14 years 4 months ago
How Many Query Superpositions Are Needed to Learn?
Abstract. This paper introduces a framework for quantum exact learning via queries, the so-called quantum protocol. It is shown that usual protocols in the classical learning setti...
Jorge Castro
COLT
2003
Springer
14 years 23 days ago
Learning with Equivalence Constraints and the Relation to Multiclass Learning
Abstract. We study the problem of learning partitions using equivalence constraints as input. This is a binary classification problem in the product space of pairs of datapoints. ...
Aharon Bar-Hillel, Daphna Weinshall
STOC
2006
ACM
122views Algorithms» more  STOC 2006»
14 years 7 months ago
Fast convergence to Wardrop equilibria by adaptive sampling methods
We study rerouting policies in a dynamic round-based variant of a well known game theoretic traffic model due to Wardrop. Previous analyses (mostly in the context of selfish routi...
Simon Fischer, Harald Räcke, Berthold Vö...