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IPCO
2004
144views Optimization» more  IPCO 2004»
13 years 9 months ago
Hedging Uncertainty: Approximation Algorithms for Stochastic Optimization Problems
Abstract. We study two-stage, finite-scenario stochastic versions of several combinatorial optimization problems, and provide nearly tight approximation algorithms for them. Our pr...
R. Ravi, Amitabh Sinha
SODA
2010
ACM
164views Algorithms» more  SODA 2010»
14 years 5 months ago
Differentially Private Approximation Algorithms
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...
APPROX
2005
Springer
136views Algorithms» more  APPROX 2005»
14 years 1 months ago
What About Wednesday? Approximation Algorithms for Multistage Stochastic Optimization
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Anupam Gupta, Martin Pál, R. Ravi, Amitabh ...
INFOCOM
1998
IEEE
13 years 12 months ago
Demand-based Radio Network Planning of Cellular Mobile Communication Systems
: This paper presents a demand-based engineering method for designing radio networks of cellularmobile communicationsystems. The proposed procedure is based on a forward-engineerin...
Kurt Tutschku
SODA
2010
ACM
174views Algorithms» more  SODA 2010»
13 years 5 months ago
Differentially Private Combinatorial Optimization
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...