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ICPR
2010
IEEE
15 years 9 months ago
Continuous Markov Random Field Optimization using Fusion Move Driven Markov Chain Monte Carlo Technique
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...
119
Voted
WAW
2009
Springer
150views Algorithms» more  WAW 2009»
15 years 9 months ago
The Giant Component in a Random Subgraph of a Given Graph
We consider a random subgraph Gp of a host graph G formed by retaining each edge of G with probability p. We address the question of determining the critical value p (as a function...
Fan Chung Graham, Paul Horn, Linyuan Lu
GECCO
2007
Springer
193views Optimization» more  GECCO 2007»
15 years 8 months ago
Approximating covering problems by randomized search heuristics using multi-objective models
The main aim of randomized search heuristics is to produce good approximations of optimal solutions within a small amount of time. In contrast to numerous experimental results, th...
Tobias Friedrich, Nils Hebbinghaus, Frank Neumann,...
ESA
2004
Springer
96views Algorithms» more  ESA 2004»
15 years 7 months ago
An Experimental Study of Random Knapsack Problems
The size of the Pareto curve for the bicriteria version of the knapsack problem is polynomial on average. This has been shown for various random input distributions. We experimenta...
René Beier, Berthold Vöcking
COCO
2006
Springer
100views Algorithms» more  COCO 2006»
15 years 6 months ago
How to Get More Mileage from Randomness Extractors
Let C be a class of distributions over {0, 1}n . A deterministic randomness extractor for C is a function E : {0, 1}n {0, 1}m such that for any X in C the distribution E(X) is sta...
Ronen Shaltiel