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» A Bayesian Approach to Tackling Hard Computational Problems
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IJCAI
2001
13 years 9 months ago
Solving Non-Boolean Satisfiability Problems with Stochastic Local Search
Much excitement has been generated by the success of stochastic local search procedures at finding solutions to large, very hard satisfiability problems. Many of the problems on wh...
Alan M. Frisch, Timothy J. Peugniez
CMSB
2006
Springer
13 years 11 months ago
Possibilistic Approach to Biclustering: An Application to Oligonucleotide Microarray Data Analysis
Abstract. The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. I...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
ICIP
2009
IEEE
13 years 5 months ago
Lamp: Linear approach for matching points
The 3D object recognition from a single or multiple 2D images is a very important problem in the computer vision field with a wide range of real applications. Considering the affi...
Manuel Marques, João Costeira
ACCV
2007
Springer
13 years 9 months ago
A Convex Programming Approach to the Trace Quotient Problem
Abstract. The trace quotient problem arises in many applications in pattern classification and computer vision, e.g., manifold learning, low-dimension embedding, etc. The task is ...
Chunhua Shen, Hongdong Li, Michael J. Brooks
CLOUDCOM
2010
Springer
13 years 5 months ago
Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems Using MapReduce
Inspired by Darwinian evolution, a genetic algorithm (GA) approach is one of the popular heuristic methods for solving hard problems, such as the Job Shop Scheduling Problem (JSSP...
Di-Wei Huang, Jimmy Lin