Results 11 to 20 of about 1,516 (207)
Multi-Agent Submodular Optimization [PDF]
CoRR, 2018 arXiv admin note: text overlap with arXiv:1612 ...
Santiago, Richard, Shepherd, F. Bruce
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Submodular Optimization with Submodular Cover and Submodular Knapsack Constraints [PDF]
CoRR, 2013 We investigate two new optimization problems -- minimizing a submodular function subject to a submodular lower bound constraint (submodular cover) and maximizing a submodular function subject to a submodular upper bound constraint (submodular knapsack).
Rishabh K. Iyer, Jeff A. Bilmes
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Migration as Submodular Optimization [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2019 Migration presents sweeping societal challenges that have recently attracted significant attention from the scientific community. One of the prominent approaches that have been suggested employs optimization and machine learning to match migrants to localities in a way that maximizes the expected number of migrants who find employment.
Paul Gölz, Ariel D. Procaccia
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Online dynamic submodular optimization [PDF]
AutomaticaWe propose new algorithms with provable performance for online binary optimization subject to general constraints and in dynamic settings. We consider the subset of problems in which the objective function is submodular. We propose the online submodular greedy algorithm (OSGA) which solves to optimality an approximation of the previous round loss ...
Antoine Lesage-Landry, Julien Pallage
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Risk-Sensitive Submodular Optimization [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2018 The conditional value at risk (CVaR) is a popular risk measure which enables risk-averse decision making under uncertainty. We consider maximizing the CVaR of a continuous submodular function, an extension of submodular set functions to a continuous domain.
Wilder, Bryan
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Submodular Optimization with Routing Constraints [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2016 Submodular optimization, particularly under cardinality or cost constraints, has received considerable attention, stemming from its breadth of application, ranging from sensor placement to targeted marketing. However, the constraints faced in many real domains are more complex.
Haifeng Zhang 0001, Yevgeniy Vorobeychik
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Submodular Functions and Optimization [PDF]
, 2005 It has widely been recognized that submodular functions play essential roles in efficiently solvable combinatorial optimization problems. Since the publication of the 1st edition of this book fifteen years ago, submodular functions have been showing ...
Fujishige, Satoru
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Optimization of Chance-Constrained Submodular Functions [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Submodular optimization plays a key role in many real-world problems. In many real-world scenarios, it is also necessary to handle uncertainty, and potentially disruptive events that violate constraints in stochastic settings need to be avoided. In this paper, we investigate submodular optimization problems with chance constraints.
Doerr, Benjamin +4 more
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Submodular Optimization with Contention Resolution Extensions. [PDF]
, 2019 This paper considers optimizing a submodular function subject to a set of downward closed constraints. Previous literature on this problem has often constructed solutions by (1) discovering a fractional solution to the multi-linear extension and (2) rounding this solution to an integral solution via a contention resolution scheme. This line of research
Benjamin Moseley, Maxim Sviridenko
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Procurement Auctions via Approximately Optimal Submodular Optimization [PDF]
CoRRWe study procurement auctions, where an auctioneer seeks to acquire services from strategic sellers with private costs. The quality of services is measured by a submodular function known to the auctioneer. Our goal is to design computationally efficient procurement auctions that (approximately) maximize the difference between the quality of the ...
Yuan Deng +5 more
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