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NETWORKS
2008
14 years 11 months ago
Reformulation and sampling to solve a stochastic network interdiction problem
The Network Interdiction Problem involves interrupting an adversary's ability to maximize flow through a capacitated network by destroying portions of the network. A budget c...
Udom Janjarassuk, Jeff Linderoth
CCE
2004
14 years 11 months ago
Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
José María Ponce-Ortega, Vicente Ric...
95
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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 5 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
STACS
2005
Springer
15 years 5 months ago
Sampling Sub-problems of Heterogeneous Max-cut Problems and Approximation Algorithms
Abstract Abstract. Recent work in the analysis of randomized approximation algorithms for NP-hard optimization problems has involved approximating the solution to a problem by the ...
Petros Drineas, Ravi Kannan, Michael W. Mahoney
BMCBI
2006
98views more  BMCBI 2006»
14 years 11 months ago
Scanning sequences after Gibbs sampling to find multiple occurrences of functional elements
Background: Many DNA regulatory elements occur as multiple instances within a target promoter. Gibbs sampling programs for finding DNA regulatory elements de novo can be prohibiti...
Kannan Tharakaraman, Leonardo Mariño-Ram&ia...