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IPCO
2004
144views Optimization» more  IPCO 2004»
14 years 11 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
KDD
2008
ACM
115views Data Mining» more  KDD 2008»
15 years 10 months ago
Topical query decomposition
We introduce the problem of query decomposition, where we are given a query and a document retrieval system, and we want to produce a small set of queries whose union of resulting...
Francesco Bonchi, Carlos Castillo, Debora Donato, ...
STOC
2005
ACM
174views Algorithms» more  STOC 2005»
15 years 10 months ago
On the average case performance of some greedy approximation algorithms for the uncapacitated facility location problem
In combinatorial optimization, a popular approach to NP-hard problems is the design of approximation algorithms. These algorithms typically run in polynomial time and are guarante...
Abraham Flaxman, Alan M. Frieze, Juan Carlos Vera
COCOON
2007
Springer
15 years 3 months ago
Priority Algorithms for the Subset-Sum Problem
Greedy algorithms are simple, but their relative power is not well understood. The priority framework [5] captures a key notion of “greediness” in the sense that it processes (...
Yuli Ye, Allan Borodin
83
Voted
SODA
2008
ACM
184views Algorithms» more  SODA 2008»
14 years 11 months ago
Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm
The problem of maximizing a concave function f(x) in a simplex S can be solved approximately by a simple greedy algorithm. For given k, the algorithm can find a point x(k) on a k-...
Kenneth L. Clarkson