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» Learning to cluster using local neighborhood structure
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ICTAI
2006
IEEE
15 years 3 months ago
Intelligent Neighborhood Exploration in Local Search Heuristics
Standard tabu search methods are based on the complete exploration of current solution neighborhood. However, for some problems with very large neighborhood or time-consuming eval...
Isabelle Devarenne, Hakim Mabed, Alexandre Caminad...
PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 1 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
PAMI
2006
156views more  PAMI 2006»
14 years 9 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
82
Voted
PPL
2010
117views more  PPL 2010»
14 years 4 months ago
Neighborhood Structures for GPU-Based Local Search Algorithms
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 ...
HEURISTICS
2002
146views more  HEURISTICS 2002»
14 years 9 months ago
Using Constraint-Based Operators to Solve the Vehicle Routing Problem with Time Windows
This paper presents operators searching large neighborhoods in order to solve the vehicle routing problem. They make use of the pruning and propagation techniques of constraint pr...
Louis-Martin Rousseau, Michel Gendreau, Gilles Pes...