Analyzing greedy vaccine allocation algorithms for metapopulation disease models. [PDF]
PLoS Computational BiologyAs observed in the case of COVID-19, effective vaccines for an emerging pandemic tend to be in limited supply initially and must be allocated strategically.
Jeffrey Keithley +3 more
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New performance guarantees for the greedy maximization of submodular set functions [PDF]
Optimization Letters, 2016 We present new tight performance guarantees for the greedy maximization of nondecreasing 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, Wolsey and Fisher (1978) and Conforti and Cornu jols ...
Jussi Laitila, Atte Moilanen
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Approximation Algorithms for Stochastic Boolean Function Evaluation and Stochastic Submodular Set Cover [PDF]
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2013 Stochastic Boolean Function Evaluation is the problem of determining the value of a given Boolean function f on an unknown input x, when each bit of x_i of x can only be determined by paying an associated cost c_i. The assumption is that x is drawn from a given product distribution, and the goal is to minimize the expected cost.
Amol Deshpande +2 more
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An improved approximation algorithm for maximizing a DR-submodular function over a convex set [PDF]
, 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 ...
Donglei Du +4 more
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Capturing Complementarity in Set Functions by Going Beyond\n Submodularity/Subadditivity [PDF]
, 2018 ITCS2019
Wei Chen, Shang‐Hua Teng, Hanrui Zhang
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Maximizing submodular set function with connectivity constraint: Theory and application to networks [PDF]
2013 Proceedings IEEE INFOCOM, 2013 In this paper, we investigate the wireless network deployment problem, which seeks the best deployment of a given limited number of wireless routers. We found that many goals for network deployment, such as maximizing the number of covered users or areas, or the total throughput of the network, can be modelled with the submodular set function ...
Tung-Wei Kuo +2 more
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On the Initial Set of Constraints for Graph-Based Submodular Function Maximization
Acta CyberneticaA crucial problem in combinatorial optimization is the submodular function maximization (SFM), and in many cases it involves graphs on which the maximization is specified. The problem is well-studied and hence there are several proposed algorithms in the literature.
Eszter Csókás, Tamás Vinkó
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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 ...
J�rgen Kindler
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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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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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