Interactive submodular set cover
, 2010 We introduce a natural generalization of submodular set cover and exact active learning with a finite hypothesis class (query learning). We call this new problem interactive submodular set cover.
Andrew Guillory, Jeff Bilmes
core
Submodular maximization and its generalization through an intersection cut lens
, 2023 We study a mixed-integer set $S:=\{(x,t) \in \{0,1\}^n \times \mathbb{R}: f(x) \ge t\}$ arising in the submodular maximization problem, where $f$ is a submodular function defined over $\{0,1\}^n$.
Liberti, Leo, Xu, Liding
core
Maximizing Submodular Set Functions Subject to Multiple Linear Constraints [PDF]
Proceedings of the Twentieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2009 Ariel Kulik, Hadas Shachnai, Tami Tamir
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Maximizing Submodular Set Function with Connectivity Constraint: Theory and Application to Networks
, 2015 —In this paper, we investigate the wireless network deployment problem, which seeks the best deployment of a given limited number of wireless routers.
Ming-jer Tsai +2 more
core
Combinatorial Algorithms for Submodular Function Minimization and Related Problems [PDF]
, 2015 Submodular functions are common in combinatorics; examples include the cut capacity function of a graph and the rank function of a matroid. The submodular function minimization problem generalizes the classical minimum cut problem and also contains a ...
Price, Christopher
core
Hypergraphs with edge-dependent vertex weights: p-Laplacians and spectral clustering. [PDF]
Front Big Data, 2023 Zhu Y, Segarra S.
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Universal set families for maximization of nonnegative submodular and XOS functions
We consider the question of designing a universal family of sets $F \subset 2^{[n]}$ such that for any function $f:2^{[n]} \to R_{\geq 0}$ in a certain class, we have $$\max_{S \in F} f(S) \geq c(n) \cdot \max_{S \subset [n]} f(S).$$ We prove that there is a family of subpolynomial size such that for any nonnegative submodular function, $c(n) = Ω ...
Chekuri, Chandra +2 more
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Distributionally robust submodular maximization
, 2020 Submodular functions have applications throughout machine learning, but in many settings, we do not have direct access to the underlying function f. We focus on stochastic functions that are given as an expectation of functions over a distribution P.
Staib, Matthew +2 more
core
Submodular maximization and its generalization through an intersection cut lens
International audienceWe study a mixed-integer set $S:={(x,t)∈{0,1}^n \times \mathbf{R}:f(x)≥t}$ arising in the submodular maximization problem, where $f$ is a submodular function defined over ${0,1}^n$.
Liberti, Leo, Xu, Liding
core +1 more source
Sequential submodular feature-sample selection for lightweight and update-efficient IoT intrusion detection. [PDF]
Sci RepAmr MN, Elliethy A, Mekkawy T, Mahran A.
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