Results 131 to 140 of about 291 (165)
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Greedy guarantees for minimum submodular cost submodular/non-submodular cover problem
Journal of Combinatorial Optimization, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Majun Shi, Zishen Yang, Wei Wang 0032
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Proceedings of the 10th ACM conference on Electronic commerce, 2009
We introduce revenue submodularity, the property that market expansion has diminishing returns on an auction's expected revenue. We prove that revenue submodularity is generally possible only in matroid markets, that Bayesian-optimal auctions are always revenue-submodular in such markets, and that the VCG mechanism is revenue-submodular in matroid ...
Shaddin Dughmi +2 more
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We introduce revenue submodularity, the property that market expansion has diminishing returns on an auction's expected revenue. We prove that revenue submodularity is generally possible only in matroid markets, that Bayesian-optimal auctions are always revenue-submodular in such markets, and that the VCG mechanism is revenue-submodular in matroid ...
Shaddin Dughmi +2 more
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On minimum submodular cover with submodular cost
Journal of Global Optimization, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hongjie Du +5 more
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On Testing Convexity and Submodularity
SIAM Journal on Computing, 2002Summary: Convex and submodular functions play an important role in many applications, and in particular in combinatorial optimization. Here we study two special cases: convexity in one dimension and submodularity in two dimensions. The latter type of functions are equivalent to the well-known Monge matrices.
Michal Parnas +2 more
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2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU), 2007
Summary form only given. Convexity is a property of real-valued functions that enable their efficient optimization. Convex optimization moreover is a problem onto which an amazing variety of practical problems can be cast. Having strong analogs to convexity, submodularity is a property of functions on discrete sets that allows their optimization to be ...
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Summary form only given. Convexity is a property of real-valued functions that enable their efficient optimization. Convex optimization moreover is a problem onto which an amazing variety of practical problems can be cast. Having strong analogs to convexity, submodularity is a property of functions on discrete sets that allows their optimization to be ...
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Directed submodularity, ditroids and directed submodular flows
Mathematical Programming, 1988Set relations and operations such as inclusion, union and intersection are generalized to directed subsets whose elements are distinguished between forward and backward elements. The concepts of submodular functions, matroids and polymatroidal network flows are extended to the concepts of directed submodular functions, ditroids and directed submodular ...
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Submodularity beyond submodular energies: Coupling edges in graph cuts
CVPR 2011, 2011We propose a new family of non-submodular global energy functions that still use submodularity internally to couple edges in a graph cut. We show it is possible to develop an efficient approximation algorithm that, thanks to the internal submodularity, can use standard graph cuts as a subroutine.
Jegelka, S., Bilmes, J.
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Management Science, 2017
We analyze the optimal allocation of trades to portfolios when the cost associated with an allocation is proportional to each portfolio’s risk. Our investigation is motivated by changes in the over-the-counter derivatives markets, under which some contracts may be traded bilaterally or through central counterparties, splitting a set of trades into two
Samim Ghamami, Paul Glasserman
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We analyze the optimal allocation of trades to portfolios when the cost associated with an allocation is proportional to each portfolio’s risk. Our investigation is motivated by changes in the over-the-counter derivatives markets, under which some contracts may be traded bilaterally or through central counterparties, splitting a set of trades into two
Samim Ghamami, Paul Glasserman
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The median partition and submodularity
Applied Mathematics and Computation, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Stochastic Submodular Maximization
2008We study stochastic submodular maximization problem with respect to a cardinality constraint. Our model can capture the effect of uncertainty in different problems, such as cascade effects in social networks, capital budgeting, sensor placement, etc. We study non-adaptive and adaptive policies and give optimal constant approximation algorithms for both
Arash Asadpour +2 more
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