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NIPS
1998
14 years 11 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
2000
Springer
15 years 2 months ago
On the Convergence Rate of Good-Turing Estimators
Good-Turing adjustments of word frequencies are an important tool in natural language modeling. In particular, for any sample of words, there is a set of words not occuring in tha...
David A. McAllester, Robert E. Schapire
ECCC
2006
97views more  ECCC 2006»
14 years 9 months ago
Runtime Analysis of a Simple Ant Colony Optimization Algorithm
Ant Colony Optimization (ACO) has become quite popular in recent years. In contrast to many successful applications, the theoretical foundation of this randomized search heuristic...
Frank Neumann, Carsten Witt
70
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COLT
2001
Springer
15 years 2 months ago
Learning Rates for Q-Learning
In this paper we derive convergence rates for Q-learning. We show an interesting relationship between the convergence rate and the learning rate used in Q-learning. For a polynomi...
Eyal Even-Dar, Yishay Mansour
SIP
2001
14 years 11 months ago
Convergence acceleration of the LMS algorithm using successive data orthogonalization
We propose a new adaptive filtering algorithm whose convergence rate is very fast even for a highly correlated input signal. It is well-known that convergence rate gets worse when...
H.-C. Shin, W.-J. Song