A. Bagchi, A. Chaudhary, R. Garg, M. T. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In Proceedings of the 7th International Workshop on Algorithms and Data Structures (WADS 2001.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... in economics and gametheory, with one of the earlier examples being the Vickrey auction [18] and VCG mechanisms [18, 9, 14] In computer science theory, recent work has given results describing truthtelling mechanisms for shortest path [1] multicast [11] load balancing [17] allocation of goods [15, 7], and allocation of digital goods [8, 13] Many of these problems can be viewed in an online setting (where requests arrive one at a time in an adversarial fashion) and only some of the earlier results consider the online scenario. There are two separate issues in dealing with combinatorial ....

A. Bagchi, A. Chaudhary, R. Garg, M. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In 7th International Workshop on Algorithms and Data Structures (WADS 2001.

....concurrent. As usual in competitive analysis [5] we will measure the performance of our online algorithms against the optimal o ine solution for the observed bid sequence. Competitive analysis of auctions (multiple buyers submitting bids to one seller) has been conducted by a number of authors [15, 10, 9, 2]. In this paper, we present the rst competitive analysis of exchanges (where there can be multiple buyers and multiple sellers submitting bids) Exchanges are a generalization of auctions one could view an exchange as a number of overlapping auctions and they give rise to additional issues. ....

A. Bagchi, A. Chaudhary, R. Garg, M. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In Proceedings of WADS 2001.

....are concurrent. As usual in competitive analysis [5] we will measure the performance of our online algorithms against the optimal offline solution for the observed bid sequence. 3 Competitive analysis of auctions (multiple buyers submitting bids to one seller) has already been conducted by others [15, 10, 9, 2], while we study exchanges where there can be multiple buyers and multiple sellers submitting bids. Our goal, for each objective function we consider, will be to produce online algorithms with optimal competitive ratios. We consider the following objectives: Maximize surplus. Each pair of buy ....

A. Bagchi, A. Chaudhary, R. Garg, M. Goodrich, and V. Numar. Seller-focused algorithms for online auctioning. In Proceedings of WADS 2001.

....concurrent. As usual in competitive analysis [5] we will measure the performance of our online algorithms against the optimal o#ine solution for the observed bid sequence. Competitive analysis of auctions (multiple buyers submitting bids to one seller) has been conducted by a number of authors [15, 10, 9, 2]. In this paper, we present the first competitive analysis of exchanges (where there can be multiple buyers and multiple sellers submitting bids) Exchanges are a generalization of auctions one could view an exchange as a number of overlapping auctions and they give rise to additional ....

A. Bagchi, A. Chaudhary, R. Garg, M. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In Proceedings of WADS 2001.

....bidder. This is re ected in nondecreasing prices for many natural situations, which is not the case when the supply is unlimited. Furthermore, Lavi and Nisan use as a benchmark the Vickrey auction [14] which Goldberg et al. 6] show is not competitive in the unlimited supply case. Bagchi et al. [1] also consider the limited supply case, though in a model where incentive compatibility is not required. In what follows, we begin in Section 2 by describing our model. In Section 3, we show that any deterministic auction performs poorly in our model. In Section 4, we give an extremely simple ....

Amitabha Bagchi, Amitabh Chaudhary, Rahul Garg, Michael T. Goodrich, and Vijay Kumar. Seller-focused algorithms for online auctioning. In Proceedings of the 7th International Workshop on Algorithms and Data Structures (WADS

....concurrent. As usual in competitive analysis [5] we will measure the performance of our online algorithms against the optimal offline solution for the observed bid sequence. 3 Competitive analysis of auctions (multiple buyers submitting bids to one seller) has already been conducted by others [15, 10, 9, 2], while we study exchanges where there can be multiple buyers and multiple sellers submitting bids. Our goal, for each objective function we consider, will be to produce online algorithms with optimal competitive ratios. We consider the following objectives: ffl Maximize surplus. Each pair of buy ....

A. Bagchi, A. Chaudhary, R. Garg, M. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In Proceedings of WADS 2001, pages 135-- 147, 2001.

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A. Bagchi, A. Chaudhary, R. Garg, M. T. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In Proceedings of the 7th International Workshop on Algorithms and Data Structures (WADS 2001.

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A. Bagchi, A. Chaudhary, R. Garg, M. T. Goodrich, and V. Kumar. Sellerfocused algorithms for online auctioning. In Proceedings of the 7th International Workshop on Algorithms and Data Structures (WADS), volume 2125. Springer Verlag LNCS, 2001. 11

....for the case of limited supply. The problem of designing online auctions for digital goods was first described by BarYossef et al. 3] one of a number of recent papers interested in analyzing revenue maximizing auctions without making statistical assumptions about the participating bidders [2, 6, 8, 10]. 1 Introduction While auctions are traditional and well studied economic mechanisms, the popularity of internet auctions has prompted wide interest in various aspects of auctions and related mechanisms, including the question of optimizing the total revenue of an auction. A number of recent ....

....various aspects of auctions and related mechanisms, including the question of optimizing the total revenue of an auction. A number of recent papers have addressed the design of revenue maximizing auctions without making any statistical assumptions about the bidders who participate in the auction [2, 3, 6, 8, 10]. A particularly interesting case is that of digital goods [8] goods of which infinitely many copies can be generated at no cost considered in the online setting by Bar Yossef et al. 3] In the model of Bar Yossef et al. 3] n bidders arrive in a sequence. Each bidder i is interested in ....

A. Bagchi, A. Chaudhary, R. Garg, M. T. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In Proceedings of the 7th International Workshop on Algorithms and Data Structures (WADS 2001.

....have analyzed auctions under the assumption that statistical information about the participating bidders is available. Recent work in computer science has been directed toward designing auctions in the absence of such statistical assumptions, using instead a form of worst case competitive analysis [2,3,6,8,10]. The proliferation of Internet auctions and the increasing availability of media on the Internet has prompted particular attention to the design of auctions for digital goods, that is, goods available in unlimited supply [6,8] In this paper, we focus on such goods, though our techniques may ....

A. Bagchi, A. Chaudhary, R. Garg, M. T. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In Proceedings of the 7th International Workshop on Algorithms and Data Structures (WADS 2001.

....of limited supply. The problem of designing online auctions for digital goods was first described by Bar Yossef et al. 3] one of a number of recent papers interested in analyzing revenue maximizing auctions without making statistical assumptions about the bidders who participate in the auction [5, 6, 4, 2]. 1 The Model In the model of Bar Yossef et al. 3] n bidders arrive in a sequence. Each bidder i is interested in one copy of the good, and values this copy at v i . The valuations are normalized to the range [1, h] so that h is the ratio between the highest and lowest valuations. Bidder i ....

Amitabha Bagchi, Amitabh Chaudhary, Rahul Garg, Michael T. Goodrich, and Vijay Kumar. Seller-focused algorithms for online auctioning. In Proceedings of the 7th International Workshop on Algorithms and Data Structures (WADS 2001.

No context found.

A. Bagchi, A. Chaudhary, R. Garg, M. Goodrich, and V. Kumar. Seller-focused algorithms for online auctioning. In 7th International Workshop on Algorithms and Data Structures (WADS 2001.

No context found.

Amitabha Bagchi, Amitabh Chaudhary, Rahul Garg, Michael T. Goodrich, and Vijay Kumar. Seller-focused algorithms for online auctioning. In F. Dehne, J.-R. Sack, and R. Tamassia, editors, Lecture Notes in Computer Science, volume 2125, chapter 4b, pages 135--147. Springer, January 2001.

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