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CORR
2010
Springer
144views Education» more  CORR 2010»
13 years 6 months ago
Fast Approximation Algorithms for Cut-based Problems in Undirected Graphs
We present a general method of designing fast approximation algorithms for cut-based minimization problems in undirected graphs. In particular, we develop a technique that given a...
Aleksander Madry
SIAMSC
2011
219views more  SIAMSC 2011»
13 years 3 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
FOCS
2004
IEEE
14 years 11 days ago
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
David B. Shmoys, Chaitanya Swamy
FOCS
2005
IEEE
14 years 2 months ago
Algorithmic Graph Minor Theory: Decomposition, Approximation, and Coloring
At the core of the seminal Graph Minor Theory of Robertson and Seymour is a powerful structural theorem capturing the structure of graphs excluding a fixed minor. This result is ...
Erik D. Demaine, Mohammad Taghi Hajiaghayi, Ken-ic...
FOCS
2004
IEEE
14 years 11 days ago
Edge-Disjoint Paths in Planar Graphs
We study the maximum edge-disjoint paths problem in undirected planar graphs: given a graph G and node pairs (demands) s1t1, s2t2, . . ., sktk, the goal is to maximize the number ...
Chandra Chekuri, Sanjeev Khanna, F. Bruce Shepherd