We present new tight performance guarantees for the greedy maximization of monotone submodular set functions. Our main result first provides a performance guarantee in terms of the overlap of the optimal and greedy solutions. As a consequence we improve performance guarantees of Nemhauser et al. (Math Program 14: 265-294, 1978) and Conforti and Cornuejols (Discr Appl Math 7: 251-274, 1984) for maximization over subsets, which are at least half the size of the problem domain. As a further application, we obtain a new tight approximation guarantee in terms of the cardinality of the problem domain.Peer reviewe
Is it possible to maximize a monotone submodular function faster than the widely used lazy greedy al...
We consider fast algorithms for monotone submodular maximization subject to a matroid constraint. We...
We present an optimal, combinatorial 1-1/e approximation algorithm for monotone submodular optimizat...
We present new tight performance guarantees for the greedy maximization of monotone submodular set f...
The greedy algorithm for monotone submodular function maximization subject to cardinality constraint...
Submodularity is a key property in discrete optimization. Submodularity has been widely used for ana...
There has been much progress recently on improved approximations for problems involving submodular o...
A litany of questions from a wide variety of scientific disciplines can be cast as non-monotone subm...
In this work we present the first practical . 1 e −ǫ . -approximation algorithm to maximise a ...
We study the problem of maximizing constrained non-monotone submodular functions and provide approxi...
We study the problem of Regularized Unconstrained Submodular Maximization (RegularizedUSM) as define...
Many problems in data mining and unsupervised machine learning take the form of minimizing a set fun...
We study the problem of maximizing a monotone non-decreasing function {Mathematical expression} subj...
We consider the problem of maximizing a (non-monotone) submodular function subject to a cardi-nality...
AbstractFor the problem maxlcub;Z(S): S is an independent set in the matroid Xrcub;, it is well-know...
Is it possible to maximize a monotone submodular function faster than the widely used lazy greedy al...
We consider fast algorithms for monotone submodular maximization subject to a matroid constraint. We...
We present an optimal, combinatorial 1-1/e approximation algorithm for monotone submodular optimizat...
We present new tight performance guarantees for the greedy maximization of monotone submodular set f...
The greedy algorithm for monotone submodular function maximization subject to cardinality constraint...
Submodularity is a key property in discrete optimization. Submodularity has been widely used for ana...
There has been much progress recently on improved approximations for problems involving submodular o...
A litany of questions from a wide variety of scientific disciplines can be cast as non-monotone subm...
In this work we present the first practical . 1 e −ǫ . -approximation algorithm to maximise a ...
We study the problem of maximizing constrained non-monotone submodular functions and provide approxi...
We study the problem of Regularized Unconstrained Submodular Maximization (RegularizedUSM) as define...
Many problems in data mining and unsupervised machine learning take the form of minimizing a set fun...
We study the problem of maximizing a monotone non-decreasing function {Mathematical expression} subj...
We consider the problem of maximizing a (non-monotone) submodular function subject to a cardi-nality...
AbstractFor the problem maxlcub;Z(S): S is an independent set in the matroid Xrcub;, it is well-know...
Is it possible to maximize a monotone submodular function faster than the widely used lazy greedy al...
We consider fast algorithms for monotone submodular maximization subject to a matroid constraint. We...
We present an optimal, combinatorial 1-1/e approximation algorithm for monotone submodular optimizat...