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IPL
1998
119views more  IPL 1998»
13 years 8 months ago
A 2.5-Factor Approximation Algorithm for the k-MST Problem
The k-MST problem requires finding that subset of at least k vertices of a given graph whose Minimum Spanning Tree has least weight amongst all subsets of at least k vertices. Th...
Sunil Arya, H. Ramesh
CCE
2004
13 years 8 months ago
An algorithmic framework for improving heuristic solutions: Part II. A new version of the stochastic traveling salesman problem
The algorithmic framework developed for improving heuristic solutions of the new version of deterministic TSP [Choi et al., 2002] is extended to the stochastic case. To verify the...
Jaein Choi, Jay H. Lee, Matthew J. Realff
CVPR
2009
IEEE
15 years 3 months ago
Alphabet SOUP: A Framework for Approximate Energy Minimization
Many problems in computer vision can be modeled using conditional Markov random fields (CRF). Since finding the maximum a posteriori (MAP) solution in such models is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
JCO
2007
128views more  JCO 2007»
13 years 8 months ago
Approximation algorithms and hardness results for labeled connectivity problems
Let G = (V, E) be a connected multigraph, whose edges are associated with labels specified by an integer-valued function L : E → N. In addition, each label ℓ ∈ N has a non-...
Refael Hassin, Jérôme Monnot, Danny S...
IPCO
1996
89views Optimization» more  IPCO 1996»
13 years 10 months ago
On Dependent Randomized Rounding Algorithms
In recent years, approximation algorithms based on randomized rounding of fractional optimal solutions have been applied to several classes of discrete optimization problems. In t...
Dimitris Bertsimas, Chung-Piaw Teo, Rakesh Vohra