Results 51 to 60 of about 11,265 (142)
Submodularity of a Set Label Disagreement Function
, 2013 A set label disagreement function is defined over the number of variables that deviates from the dominant label. The dominant label is the value assumed by the largest number of variables within a set of binary variables. The submodularity of a certain family of set label disagreement function is discussed in this manuscript. Such disagreement function
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Maximizing General Set Functions by Submodular Decomposition
, 2009 We present a branch and bound method for maximizing an arbitrary set function h mapping 2^V to R. By decomposing h as f-g, where f is a submodular function and g is the cut function of a (simple, undirected) graph G with vertex set V, our original problem is reduced to a sequence of submodular maximization problems.
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Approximation Algorithms for Stochastic Submodular Set Cover with Applications to Boolean Function Evaluation and Min-Knapsack [PDF]
ACM Transactions on Algorithms, 2016 We present a new approximation algorithm for the stochastic submodular set cover (SSSC) problem called adaptive dual greedy . We use this algorithm to obtain a 3-approximation algorithm solving the stochastic Boolean function evaluation (SBFE) problem for linear threshold formulas (LTFs).
Amol Deshpande +2 more
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A Mazur-Orlicz type theorem for submodular set functions
Journal of Mathematical Analysis and Applications, 1986 Let \({\mathcal L}\) be a lattice of subsets of a given set \(\Omega\) with \(\emptyset \in {\mathcal L}\). A function \(\gamma:{\mathcal L}\to {\mathbb{R}}\cup \{- \infty \}\) is called a submodular (modular) set function if \(\gamma (\emptyset)=0\) and \[ \gamma (A\cup B)+\gamma (A\cap B)\leq (=)\gamma (A)+\gamma (B),\quad A\in {\mathcal L},\quad B ...
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An improved approximation algorithm for maximizing a DR-submodular function over a convex set
, 2022 Maximizing a DR-submodular function subject to a general convex set is an NP-hard problem arising from many applications in combinatorial optimization and machine learning. While it is highly desirable to design efficient approximation algorithms under this general setting where neither the objective function is monotonic nor the feasible set is down ...
Du, Donglei +4 more
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The Maximum Traveling Salesman Problem with Submodular Rewards [PDF]
, 2012 In this paper, we look at the problem of finding the tour of maximum reward on an undirected graph where the reward is a submodular function, that has a curvature of $\kappa$, of the edges in the tour. This problem is known to be NP-hard.
Jawaid Stephen, L. Smith, Syed Talha
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Capturing Complementarity in Set Functions by Going Beyond Submodularity/Subadditivity
, 2018 ITCS2019
Chen, Wei +2 more
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Journal of Numerical Analysis and Approximation Theory, 2018 In this paper, for the univariate Bernstein-Kantorovich-Choquet, Szasz-Kantorovich-Choquet, Baskakov-Kantorovich-Choquet and Bernstein-Durrmeyer-Choquet operators written in terms of the Choquet integrals with respect to monotone and submodular set ...
Sorin Gal
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A Combinatorial, Strongly Polynomial-Time Algorithm for Minimizing Submodular Functions
, 2000 This paper presents the first combinatorial polynomial-time algorithm for minimizing submodular set functions, answering an open question posed in 1981 by Grotschel, Lovasz, and Schrijver.
Fleischer, Lisa +2 more
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Journal of Mathematical Analysis and Applications, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gal, Sorin G., Opris, Bogdan D.
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