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Bayesian combinatorial auctions: Expanding single buyer mechanisms to many buyers
 In FOCS. 512–521
"... • Bronze Medal, 13th International Olympiad in Informatics, Tampere, Finland, ..."
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• Bronze Medal, 13th International Olympiad in Informatics, Tampere, Finland,
Expressive Banner Ad Auctions and ModelBased Online Optimization for Clearing
"... We present the design of a banner advertising auction which is considerably more expressive than current designs. We describe a general model of expressive ad contracts/bidding and an allocation model that can be executed in real time through the assignment of fractions of relevant ad channels to sp ..."
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Cited by 15 (9 self)
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We present the design of a banner advertising auction which is considerably more expressive than current designs. We describe a general model of expressive ad contracts/bidding and an allocation model that can be executed in real time through the assignment of fractions of relevant ad channels to specific advertiser contracts. The uncertainty in channel supply and demand is addressed by the formulation of a stochastic combinatorial optimization problem for channel allocation that is rerun periodically. We solve this in two different ways: fast deterministic optimization with respect to expectations; and a novel online samplebased stochastic optimization method— that can be applied to continuous decision spaces—which exploits the deterministic optimization as a black box. Experiments demonstrate the importance of expressive bidding and the value of stochastic optimization. 1
SelfCorrecting SamplingBased Dynamic MultiUnit Auctions
"... We exploit methods of samplebased stochastic optimization for the purpose of strategyproof dynamic, multiunit auctions. There are no analytic characterizations of optimal policies for this domain and thus a heuristic approach, such as that proposed here, seems necessary in practice. Following the ..."
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Cited by 11 (4 self)
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We exploit methods of samplebased stochastic optimization for the purpose of strategyproof dynamic, multiunit auctions. There are no analytic characterizations of optimal policies for this domain and thus a heuristic approach, such as that proposed here, seems necessary in practice. Following the suggestion of Parkes and Duong [17], we perform sensitivity analysis on the allocation decisions of an online algorithm for stochastic optimization, and correct the decisions to enable a strategyproof auction. In applying this approach to the allocation of nonexpiring goods, the technical problem that we must address is related to achieving strategyproofness for reports of departure. This cannot be achieved through selfcorrection without canceling many allocation decisions, and must instead be achieved by first modifying the underlying algorithm. We introduce the NowWait method for this purpose, prove its successful interfacing with sensitivity analysis and demonstrate good empirical performance. Our method is quite general, requiring a technical property of uncertainty independence, and that values are not too positively correlated with agent patience. We also show how to incorporate “virtual valuations ” in order to increase the seller’s revenue. 1
Submodular Secretary Problem and Extensions
"... Online auction is the essence of many modern markets, particularly networked markets, in which information about goods, agents, and outcomes is revealed over a period of time, and the agents must make irrevocable decisions without knowing future information. Optimal stopping theory, especially the c ..."
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Cited by 9 (1 self)
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Online auction is the essence of many modern markets, particularly networked markets, in which information about goods, agents, and outcomes is revealed over a period of time, and the agents must make irrevocable decisions without knowing future information. Optimal stopping theory, especially the classic secretary problem, is a powerful tool for analyzing such online scenarios which generally require optimizing an objective function over the input. The secretary problem and its generalization the multiplechoice secretary problem were under a thorough study in the literature. In this paper, we consider a very general setting of the latter problem called the submodular secretary problem, in which the goal is to select k secretaries so as to maximize the expectation of a (not necessarily monotone) submodular function which defines efficiency of the selected secretarial group based on their overlapping skills. We present the first constantcompetitive algorithm for this case. In a more general setting in which selected secretaries should form an independent (feasible) set in each of l given matroids as well, we obtain an O(l log² r)competitive algorithm generalizing several previous results, where r is the maximum rank of the matroids. Another generalization is to consider l knapsack constraints (i.e., a knapsack constraint assigns a nonnegative cost to each secretary, and requires that the total cost of all the secretaries employed be no more than a budget value) instead of the matroid constraints, for which we present an O(l)competitive algorithm. In a sharp contrast, we show for a more general setting of subadditive secretary problem, there is no õ ( √ n)competitive algorithm and thus submodular functions are the most general functions to consider for constantcompetitiveness in our setting. We complement this result by giving a matching O ( √ n)competitive algorithm for the subadditive case. At the end, we consider some special cases of our general setting as well.
On Revenue in the Generalized Second Price Auction
"... The Generalized Second Price (GSP) auction is the primary auction used for selling sponsored search advertisements. In this paper we consider the revenue of this auction at equilibrium. Most previous work on the revenue of GSP focuses on envy free equilibria of the full information version of this g ..."
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The Generalized Second Price (GSP) auction is the primary auction used for selling sponsored search advertisements. In this paper we consider the revenue of this auction at equilibrium. Most previous work on the revenue of GSP focuses on envy free equilibria of the full information version of this game. Envyfree equilibria are known to obtain at least the revenue of the VCG auction. Here we consider revenue in equilibria that are not envyfree, as well as in equilibria for the Bayesian, partial information version of this game. Weshowthat,atanyNashequilibriumofthefullinformation game, the GSP auction obtains at least half of the revenueof the VCG mechanism excluding the payment of a single participant. This bound is tight, and we give examples demonstrating that GSP cannot approximate the full revenue of
On Variants of the Matroid Secretary Problem
"... Abstract. We present a number of positive and negative results for variants of the matroid secretary problem. Most notably, we design a constantfactorcompetitivealgorithmforthe“randomassignment”model where the weights are assigned randomly to the elements of a matroid, and then the elements arrive ..."
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Abstract. We present a number of positive and negative results for variants of the matroid secretary problem. Most notably, we design a constantfactorcompetitivealgorithmforthe“randomassignment”model where the weights are assigned randomly to the elements of a matroid, and then the elements arrive online in an adversarial order (extending a result of Soto [20]). This is under the assumption that the matroid is known in advance. If the matroid is unknown in advance, we present an O(logrlogn)approximation, and prove that a better than O(logn/loglogn) approximation is impossible. This resolves an open question posed by Babaioff et al. [3]. As a natural special case, we also consider the classical secretary problem where the number of candidates n is unknown in advance. If n is chosen by an adversary from {1,...,N}, we provide a nearly tight answer, by providing an algorithm that chooses the best candidate with probability at least 1/(HN−1 + 1) and prove that a probability better than 1/HN cannot be achieved (where HN is the Nth harmonic number). 1
Auction protocols
"... The word “auction ” generally refers to a mechanism for allocating one or more resources to one or more parties (or bidders). Generally, once the allocation is determined, some amount of money changes hands; the precise monetary transfers are determined by the auction process. While in some auction ..."
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Cited by 1 (1 self)
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The word “auction ” generally refers to a mechanism for allocating one or more resources to one or more parties (or bidders). Generally, once the allocation is determined, some amount of money changes hands; the precise monetary transfers are determined by the auction process. While in some auction protocols, such as the English auction, bidders repeatedly increase their bids in an attempt to outbid each other, this is not an essential component of an auction. There are many other auction protocols, and we will study some of them in this chapter. Auctions have traditionally been studied mostly by economists. In recent years, computer scientists have also become interested in auctions, for a variety of reasons. Auctions can be useful for allocating various computing resources across users. In artificial intelligence, they can be used to allocate resources and tasks across multiple artificially intelligent “agents. ” Auctions are also important in electronic commerce: there are of course several wellknown auction websites, but additionally, search engines use auctions to sell advertising space on their results pages. Finally, increased computing power and improved algorithms have made new types of auctions possible—most notably combinatorial auctions, in which
Advances in Economics and Econometrics: Theory and Application, Ninth World Congress (Econometric Society
, 2007
"... conditions: existence and correspondence theorems for ..."
Expressiveness and Optimization under Incentive Compatibility Constraints in Dynamic Auctions
, 2009
"... This thesis designs and analyzes auctions for persistent goods in three domains with arriving and departing bidders, quantifying tradeoffs between design objectives. The central objective is incentive compatibility, ensuring that it is in bidders’ best interest to reveal their private information tr ..."
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This thesis designs and analyzes auctions for persistent goods in three domains with arriving and departing bidders, quantifying tradeoffs between design objectives. The central objective is incentive compatibility, ensuring that it is in bidders’ best interest to reveal their private information truthfully. Other primary concerns are expressiveness, i.e. the richness of the effective bidding language, and optimization, in the form of aiming towards high revenue or high value of the allocation of goods to bidders. In the first domain, an arriving bidder requests a fixed number of goods by his departure, introducing combinatorial constraints. I achieve the global property of incentive compatibility via selfcorrection, a local verification procedure, applied to a heuristic modification of an online stochastic algorithm. This heuristic is flexible and has encouraging empirical performance in terms of allocation value, revenue and computation overhead. In the second domain, impatient buyers make instantaneous reservation offers for future goods. Introducing the practical ability of cancellations by the seller leads to an auction with worstcase guarantees without any assumption on the sequence of offers. A