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Auctions with revenue guarantees for sponsored search
 Workshop on Sponsored Search Auctions
, 2007
"... We consider the problem of designing auctions for sponsored search with revenue guarantees. We first analyze two randomsampling auctions in this setting and derive high competitive ratios against the optimal revenue from two classes of omniscient auctions: singleprice auctions, restricted to charg ..."
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Cited by 8 (1 self)
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We consider the problem of designing auctions for sponsored search with revenue guarantees. We first analyze two randomsampling auctions in this setting and derive high competitive ratios against the optimal revenue from two classes of omniscient auctions: singleprice auctions, restricted to charging a single price per click and weightedprice auctions, restricted to charging prices inversely proportional to the advertisement’s clickability. Either of these benchmark revenues can be larger, and this cannot be determined without knowing the private valuations of the bidders. We combine these two asymptotically nearoptimal auctions into a single auction with the following properties: the auction has a Nash equilibrium and every equilibrium has revenue at least the larger of the revenues raised by running each of the two auctions individually (assuming bidders bid truthfully when doing so is a utility maximizing strategy). Simulations indicate that our auctions outperform the VCG auction in less competitive markets.
Optimal efficiency guarantees for network design mechanisms
 In Proceedings of the 12th Conference on Integer Programming and Combinatorial Optimization (IPCO), volume 4513 of Lecture Notes in Computer Science
, 2007
"... Abstract. A costsharing problem is defined by a set of players vying to receive some good or service, and a cost function describing the cost incurred by the auctioneer as a function of the set of winners. A costsharing mechanism is a protocol that decides which players win the auction and at what ..."
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Cited by 6 (1 self)
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Abstract. A costsharing problem is defined by a set of players vying to receive some good or service, and a cost function describing the cost incurred by the auctioneer as a function of the set of winners. A costsharing mechanism is a protocol that decides which players win the auction and at what prices. Three desirable but provably mutually incompatible properties of a costsharing mechanism are: incentivecompatibility, meaning that players are motivated to bid their true private value for receiving the good; budgetbalance, meaning that the mechanism recovers its incurred cost with the prices charged; and efficiency, meaning that the cost incurred and the value to the players served are traded off in an optimal way. Our work is motivated by the following fundamental question: for which costsharing problems are incentivecompatible mechanisms with good approximate budgetbalance and efficiency possible? We focus on cost functions defined implicitly by NPhard combinatorial optimization problems, including the metric uncapacitated facility location problem, the Steiner tree problem, and rentorbuy network design problems. For facility location and rentorbuy network design, we establish for the first time that approximate budgetbalance and efficiency are simultaneously possible. For the Steiner tree problem, where such a guarantee was previously known, we prove a new, optimal lower bound on the approximate efficiency achievable by the wide and natural class of “Moulin mechanisms”. This lower bound exposes a latent approximation hierarchy among different costsharing problems. 1
Quantifying Inefficiency in CostSharing Mechanisms
, 2009
"... In a costsharing problem, several participants with unknown preferences vie to receive some good or service, and each possible outcome has a known cost. A costsharing mechanism is a protocol that decides which participants are allocated a good and at what prices. Three desirable properties of a co ..."
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Cited by 3 (0 self)
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In a costsharing problem, several participants with unknown preferences vie to receive some good or service, and each possible outcome has a known cost. A costsharing mechanism is a protocol that decides which participants are allocated a good and at what prices. Three desirable properties of a costsharing mechanism are: incentivecompatibility, meaning that participants are motivated to bid their true private value for receiving the good; budgetbalance, meaning that the mechanism recovers its incurred cost with the prices charged; and economic efficiency, meaning that the cost incurred and the value to the participants are traded off in an optimal way. These three goals have been known to be mutually incompatible for thirty years. Nearly all the work on costsharing mechanism design by the economics and computer science communities has focused on achieving two of these goals while completely ignoring the third. We introduce novel measures for quantifying efficiency loss in costsharing mechanisms and prove simultaneous approximate budgetbalance and approximate efficiency guarantees for mechanisms for a wide range of costsharing problems, including all submodular and Steiner tree problems. Our key technical tool is an exact characterization of worstcase efficiency loss in Moulin mechanisms, the dominant paradigm in costsharing mechanism design.
Balloon Popping With Applications to Ascending Auctions
"... We study the power of ascending auctions in a scenario in which a seller is selling a collection of identical items to anonymous unitdemand bidders. We show that even with full knowledge of the set of bidders ’ private valuations for the items, if the bidders are exante identical, no ascending auc ..."
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We study the power of ascending auctions in a scenario in which a seller is selling a collection of identical items to anonymous unitdemand bidders. We show that even with full knowledge of the set of bidders ’ private valuations for the items, if the bidders are exante identical, no ascending auction can extract more than a constant times the revenue of the best fixed price scheme. This problem is equivalent to the problem of coming up with an optimal strategy for blowing up indistinguishable balloons with known capacities in order to maximize the amount of contained air. We show that the algorithm which simply inflates all balloons to a fixed volume is close to optimal in this setting.