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NETWORKS
2008
13 years 7 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
13 years 7 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...
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
14 years 1 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
14 years 28 days 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»
13 years 7 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...