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FSTTCS
2004
Springer
13 years 11 months ago
Improved Approximation Algorithms for Maximum Graph Partitioning Problems
Abstract Abstract. In this paper we improve the analysis of approximation algorithms based on semidefinite programming for the maximum graph partitioning problems MAX-k-CUT, MAX-k...
Gerold Jäger, Anand Srivastav
BMCBI
2010
144views more  BMCBI 2010»
13 years 6 months ago
Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data
Background: The investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuc...
Petr Novák, Pavel Neumann, Jirí Maca...
COLT
2007
Springer
14 years 13 days ago
Resource-Bounded Information Gathering for Correlation Clustering
We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in w...
Pallika Kanani, Andrew McCallum
CVPR
2010
IEEE
14 years 1 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
STACS
2005
Springer
13 years 11 months ago
Sampling Sub-problems of Heterogeneous Max-cut Problems and Approximation Algorithms
Abstract Abstract. Recent work in the analysis of randomized approximation algorithms for NP-hard optimization problems has involved approximating the solution to a problem by the ...
Petros Drineas, Ravi Kannan, Michael W. Mahoney