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124
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MOR
2007
109views more  MOR 2007»
15 years 3 months ago
Solution and Forecast Horizons for Infinite-Horizon Nonhomogeneous Markov Decision Processes
We consider the problem of solving a nonhomogeneous infinite horizon Markov Decision Process (MDP) problem in the general case of potentially multiple optimal first period polic...
Torpong Cheevaprawatdomrong, Irwin E. Schochetman,...
111
Voted
AAAI
2010
15 years 5 months ago
Smooth Optimization for Effective Multiple Kernel Learning
Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu...
141
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GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
15 years 7 months ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace
112
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INFOCOM
2010
IEEE
15 years 1 months ago
Markov Approximation for Combinatorial Network Optimization
—Many important network design problems can be formulated as a combinatorial optimization problem. A large number of such problems, however, cannot readily be tackled by distribu...
Minghua Chen, Soung Chang Liew, Ziyu Shao, Caihong...
152
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GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
15 years 9 months ago
A new evolutionary model for detecting multiple optima
Multimodal optimization problems consist in detecting all global and local optima of a problem. A new evolutionary approach to multimodal optimization called Roaming technique (RO...
Rodica Ioana Lung, D. Dumitrescu