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125
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ICML
2002
IEEE
16 years 3 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans
142
Voted
PPSC
1989
15 years 3 months ago
Evaluating Block Algorithm Variants in LAPACK
The LAPACK software project currently under development is intended to provide a portable linear algebra library for high performance computers. LAPACK will make use of the Level 1...
Ed Anderson, Jack Dongarra
120
Voted
EMMCVPR
2001
Springer
15 years 6 months ago
An Experimental Comparison of Min-cut/Max-flow Algorithms for Energy Minimization in Vision
After [15, 31, 19, 8, 25, 5] minimum cut/maximum flow algorithms on graphs emerged as an increasingly useful tool for exact or approximate energy minimization in low-level vision...
Yuri Boykov, Vladimir Kolmogorov
126
Voted
EVOW
2010
Springer
15 years 9 months ago
Parameter Tuning of Evolutionary Algorithms: Generalist vs. Specialist
Abstract. Finding appropriate parameter values for Evolutionary Algorithms (EAs) is one of the persistent challenges of Evolutionary Computing. In recent publications we showed how...
Selmar K. Smit, A. E. Eiben
105
Voted
AEI
2005
99views more  AEI 2005»
15 years 2 months ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson