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» An Online Algorithm for Maximizing Submodular Functions
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CORR
2010
Springer
111views Education» more  CORR 2010»
13 years 5 months ago
Submodular Maximization by Simulated Annealing
We consider the problem of maximizing a nonnegative (possibly non-monotone) submodular set function with or without constraints. Feige et al. [9] showed a 2/5-approximation for th...
Shayan Oveis Gharan, Jan Vondrák
FOCS
2009
IEEE
13 years 11 months ago
Symmetry and Approximability of Submodular Maximization Problems
Abstract— A number of recent results on optimization problems involving submodular functions have made use of the ”multilinear relaxation” of the problem [3], [8], [24], [14]...
Jan Vondrák
JMLR
2010
187views more  JMLR 2010»
12 years 11 months ago
SFO: A Toolbox for Submodular Function Optimization
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
Andreas Krause
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
11 years 7 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
APPROX
2009
Springer
138views Algorithms» more  APPROX 2009»
13 years 11 months ago
Submodular Maximization over Multiple Matroids via Generalized Exchange Properties
Submodular-function maximization is a central problem in combinatorial optimization, generalizing many important NP-hard problems including Max Cut in digraphs, graphs and hypergr...
Jon Lee, Maxim Sviridenko, Jan Vondrák