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CVPR
1998
IEEE
14 years 11 months ago
Markov Random Fields with Efficient Approximations
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
Yuri Boykov, Olga Veksler, Ramin Zabih
CORR
2008
Springer
107views Education» more  CORR 2008»
13 years 10 months ago
Symmetry Breaking for Maximum Satisfiability
Symmetries are intrinsic to many combinatorial problems including Boolean Satisfiability (SAT) and Constraint Programming (CP). In SAT, the identification of symmetry breaking pred...
João Marques-Silva, Inês Lynce, Vasco...
TCBB
2008
122views more  TCBB 2008»
13 years 9 months ago
Mixed Integer Linear Programming for Maximum-Parsimony Phylogeny Inference
Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new adva...
Srinath Sridhar, Fumei Lam, Guy E. Blelloch, R. Ra...
HEURISTICS
2002
146views more  HEURISTICS 2002»
13 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...
CSCLP
2007
Springer
14 years 4 months ago
Preference-Based Problem Solving for Constraint Programming
Abstract. Combinatorial problems such as scheduling, resource allocation, and configuration have many attributes that can be subject of user preferences. Traditional optimization ...
Ulrich Junker