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IPPS
2010
IEEE
13 years 4 months ago
Large neighborhood local search optimization on graphics processing units
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as &q...
Thé Van Luong, Nouredine Melab, El-Ghazali ...
IJAR
2010
113views more  IJAR 2010»
13 years 4 months ago
A geometric view on learning Bayesian network structures
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Milan Studený, Jirí Vomlel, Raymond ...
PAMI
2006
156views more  PAMI 2006»
13 years 6 months ago
Robust Point Matching for Nonrigid Shapes by Preserving Local Neighborhood Structures
In previous work on point matching, a set of points is often treated as an instance of a joint distribution to exploit global relationships in the point set. For nonrigid shapes, h...
Yefeng Zheng, David S. Doermann
STOC
2004
ACM
153views Algorithms» more  STOC 2004»
14 years 6 months ago
Quantum and classical query complexities of local search are polynomially related
Let f be an integer valued function on a finite set V . We call an undirected graph G(V, E) a neighborhood structure for f. The problem of finding a local minimum for f can be phr...
Miklos Santha, Mario Szegedy
AAAI
2000
13 years 7 months ago
Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search
Local search algorithms often get trapped in local optima. Algorithms such as tabu search and simulated annealing 'escape' local optima by accepting nonimproving moves. ...
Laura Barbulescu, Jean-Paul Watson, L. Darrell Whi...