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FSTTCS
2006
Springer
14 years 1 months ago
Approximation Algorithms for 2-Stage Stochastic Optimization Problems
Abstract. Stochastic optimization is a leading approach to model optimization problems in which there is uncertainty in the input data, whether from measurement noise or an inabili...
Chaitanya Swamy, David B. Shmoys
PODC
2005
ACM
14 years 3 months ago
Facility location: distributed approximation
In this paper, we initiate the study of the approximability of the facility location problem in a distributed setting. In particular, we explore a trade-off between the amount of...
Thomas Moscibroda, Roger Wattenhofer
CORR
2012
Springer
218views Education» more  CORR 2012»
12 years 5 months ago
Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
Yaniv Plan, Roman Vershynin
MP
2006
119views more  MP 2006»
13 years 9 months ago
Approximate extended formulations
Mixed integer programming (MIP) formulations are typically tightened through the use of a separation algorithm and the addition of violated cuts. Using extended formulations involv...
Mathieu Van Vyve, Laurence A. Wolsey
ESOP
2007
Springer
14 years 4 months ago
Interprocedurally Analysing Linear Inequality Relations
In this paper we present an alternative approach to interprocedurally g linear inequality relations. We propose an abstraction of the effects of procedures through convex sets of t...
Helmut Seidl, Andrea Flexeder, Michael Petter