Jul 28, 2024 · In this work, we focus on maximizing the stochastic DS decomposition problem. If the constraint is a uniform matroid, we design an adaptive policy.
Maximizing stochastic set function under a matroid constraint from ...
ideas.repec.org › spr › jcomop
In this work, we focus on maximizing the stochastic DS decomposition problem. If the constraint is a uniform matroid, we design an adaptive policy, namely ...
Jul 28, 2024 · In this work, we focus on maximizing the stochastic DS decomposition problem. If the constraint is a uniform matroid, we design an adaptive ...
Jul 28, 2024 · Building on these groundbreaking works, the submodular maximization problem has been widely used to address application.
Oct 22, 2024 · In this work, we focus on maximizing the stochastic DS decomposition problem. If the constraint is a uniform matroid, we design an adaptive ...
Maximizing stochastic set function under a matroid constraint from decomposition. Shengminjie Chen. ,. Donglei Du. ,. Wenguo Yang. ,. Suixiang Gao.
Maximizing stochastic set function under a matroid constraint from decomposition. Journal of Combinatorial Optimization, Vol. 48, No. 1 | 28 July 2024.
Dec 18, 2015 · We study the problem of maximizing a stochastic monotone submodular function with respect to a matroid constraint.
For the problem of maximizing a submodular function subject to a matroid constraint (special case of p = 1), the greedy algorithm achieves a ratio of 1/2.
Missing: stochastic decomposition.
Unlike submodular minimization, submodular maximization is NP-hard. In this paper, we give the first constant-factor approximation algorithm for maximizing any ...