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FOCS
2005
IEEE
13 years 11 months ago
How to Pay, Come What May: Approximation Algorithms for Demand-Robust Covering Problems
Robust optimization has traditionally focused on uncertainty in data and costs in optimization problems to formulate models whose solutions will be optimal in the worstcase among ...
Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Sing...
MOC
2002
120views more  MOC 2002»
13 years 5 months ago
Analysis of iterative methods for saddle point problems: a unified approach
In this paper two classes of iterative methods for saddle point problems are considered: inexact Uzawa algorithms and a class of methods with symmetric preconditioners. In both cas...
Walter Zulehner
APPROX
2006
Springer
162views Algorithms» more  APPROX 2006»
13 years 9 months ago
Approximating Precedence-Constrained Single Machine Scheduling by Coloring
Abstract. This paper investigates the relationship between the dimension theory of partial orders and the problem of scheduling precedenceconstrained jobs on a single machine to mi...
Christoph Ambühl, Monaldo Mastrolilli, Ola Sv...
ESA
2010
Springer
140views Algorithms» more  ESA 2010»
13 years 6 months ago
A Unified Approach to Approximate Proximity Searching
The inability to answer proximity queries efficiently for spaces of dimension d > 2 has led to the study of approximation to proximity problems. Several techniques have been pro...
Sunil Arya, Guilherme Dias da Fonseca, David M. Mo...
NIPS
2007
13 years 7 months ago
What makes some POMDP problems easy to approximate?
Point-based algorithms have been surprisingly successful in computing approximately optimal solutions for partially observable Markov decision processes (POMDPs) in high dimension...
David Hsu, Wee Sun Lee, Nan Rong