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940
Revenue Submodularity
 EC'09
, 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 Bayesianoptimal auctions are always revenuesubmodular in such markets, and that t ..."
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Cited by 22 (8 self)
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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 Bayesianoptimal auctions are always revenuesubmodular in such markets
Strategyproof Sharing of Submodular Costs: budget balance versus efficiency
, 1999
"... A service is produced for a set of agents. The service is binary, each agent either receives service or not, and the total cost of service is a submodular function of the set receiving service. We investigate strategyproof mechanisms that elicit individual willingness to pay, decide who is served ..."
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Cited by 198 (18 self)
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A service is produced for a set of agents. The service is binary, each agent either receives service or not, and the total cost of service is a submodular function of the set receiving service. We investigate strategyproof mechanisms that elicit individual willingness to pay, decide who
Submodular Stochastic Probing on Matroids
"... In a stochastic probing problem we are given a universe E, where each element e ∈ E is active independently with probability pe ∈ [0, 1], and only a probe of e can tell us whether it is active or not. On this universe we execute a process that one by one probes elements — if a probed element is acti ..."
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Cited by 3 (1 self)
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submodular objective function. We give a (1 − 1/e)/(kin + kout + 1)approximation algorithm for the case in which we are given kin ≥ 0 matroids as inner constraints and kout ≥ 1 matroids as outer constraints. There are two main ingredients behind this result. First is a previously unpublished stronger bound
Sharing the Cost of Multicast Transmissions
, 2001
"... We investigate costsharing algorithms for multicast transmission. Economic considerations point to two distinct mechanisms, marginal cost and Shapley value, as the two solutions most appropriate in this context. We prove that the former has a natural algorithm that uses only two messages per link o ..."
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Cited by 291 (19 self)
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We investigate costsharing algorithms for multicast transmission. Economic considerations point to two distinct mechanisms, marginal cost and Shapley value, as the two solutions most appropriate in this context. We prove that the former has a natural algorithm that uses only two messages per link of the multicast tree, while we give evidence that the latter requires a quadratic total number of messages. We also show that the welfare value achieved by an optimal multicast tree is NPhard to approximate within any constant factor, even for boundeddegree networks. The lowerbound proof for the Shapley value uses a novel algebraic technique for bounding from below the number of messages exchanged in a distributed computation; this technique may prove useful in other contexts as well.
Maximization of NonMonotone Submodular Functions
"... A litany of questions from a wide variety of scientific disciplines can be cast as nonmonotone submodular maximization problems. Since this class of problems includes maxcut, it is NPhard. Thus, generalpurpose algorithms for the class tend to be approximation algorithms. For unconstrained probl ..."
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A litany of questions from a wide variety of scientific disciplines can be cast as nonmonotone submodular maximization problems. Since this class of problems includes maxcut, it is NPhard. Thus, generalpurpose algorithms for the class tend to be approximation algorithms. For unconstrained
Online submodular maximization under a matroid constraint . . .
, 2014
"... Which ads should we display in sponsored search in order to maximize our revenue? How should we dynamically rank information sources to maximize the value of the ranking? These applications exhibit strong diminishing returns: Redundancy decreases the marginal utility of each ad or information source ..."
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Which ads should we display in sponsored search in order to maximize our revenue? How should we dynamically rank information sources to maximize the value of the ranking? These applications exhibit strong diminishing returns: Redundancy decreases the marginal utility of each ad or information
On the approximability of budgeted allocations and improved lower bounds for submodular welfare maximization and GAP
 In Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer ScienceVolume 00
, 2008
"... In this paper we consider the following maximum budgeted allocation(MBA) problem: Given a set of m indivisible items and n agents; each agent i willing to pay bij on item j and with a maximum budget of Bi, the goal is to allocate items to agents to maximize revenue. The problem naturally arises as a ..."
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Cited by 36 (3 self)
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In this paper we consider the following maximum budgeted allocation(MBA) problem: Given a set of m indivisible items and n agents; each agent i willing to pay bij on item j and with a maximum budget of Bi, the goal is to allocate items to agents to maximize revenue. The problem naturally arises
Item Pricing for Revenue Maximization
"... We consider the problem of pricing n items to maximize revenue when faced with a series of unknown buyers with complex preferences, and show that a simple pricing scheme achieves surprisingly strong guarantees. We show that in the unlimited supply setting, a random single price achieves expected rev ..."
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Cited by 41 (6 self)
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We consider the problem of pricing n items to maximize revenue when faced with a series of unknown buyers with complex preferences, and show that a simple pricing scheme achieves surprisingly strong guarantees. We show that in the unlimited supply setting, a random single price achieves expected
Secondary spectrum auctions for symmetric and submodular bidders
 In Proc. 13th Conf. Electronic Commerce (EC
, 2012
"... ar ..."
Nonmonotone submodular maximization under matroid and knapsack constraints
 In Proc. 41th ACM Symp. on Theory of Computing
, 2009
"... Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hypergraphs, certain constraint satisfaction problems, maximum entropy sampling, and maximum facility location problems. Un ..."
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Cited by 37 (1 self)
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Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hypergraphs, certain constraint satisfaction problems, maximum entropy sampling, and maximum facility location problems
Results 1  10
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940