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ECCV
2008
Springer
15 years 11 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 1 months ago
Epsilon-constraint with an efficient cultured differential evolution
In this paper we present the use of a previously developed single-objective optimization approach, together with the -constraint method, to provide an approximation of the Pareto ...
Ricardo Landa Becerra, Carlos A. Coello Coello
UAI
2008
14 years 11 months ago
Partitioned Linear Programming Approximations for MDPs
Approximate linear programming (ALP) is an efficient approach to solving large factored Markov decision processes (MDPs). The main idea of the method is to approximate the optimal...
Branislav Kveton, Milos Hauskrecht
SSDBM
2010
IEEE
133views Database» more  SSDBM 2010»
14 years 7 months ago
PrefIndex: An Efficient Supergraph Containment Search Technique
Graphs are prevailingly used in many applications to model complex data structures. In this paper, we study the problem of supergraph containment search. To avoid the NP-complete s...
Gaoping Zhu, Xuemin Lin, Wenjie Zhang, Wei Wang, H...
CORR
2010
Springer
152views Education» more  CORR 2010»
14 years 9 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná