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10,578
Posting prices with unknown distributions
 IN INNOVATIONS IN COMPUTER SCIENCE (ICS), 2011. [BH08] L. BLUMROSEN AND
"... We consider a dynamic auction model, where bidders sequentially arrive to the market. The values of the bidders for the item for sale are independently drawn from a distribution, but this distribution is unknown to the seller. The seller offers a takeitorleaveit price for each arriving bidder ..."
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Cited by 5 (0 self)
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We consider a dynamic auction model, where bidders sequentially arrive to the market. The values of the bidders for the item for sale are independently drawn from a distribution, but this distribution is unknown to the seller. The seller offers a takeitorleaveit price for each arriving bidder
Online bipartite matching with unknown distributions
 In STOC
, 2011
"... We consider the online bipartite matching problem in the unknown distribution input model. We show that the Ranking algorithm of [KVV90] achieves a competitive ratio of at least 0.653. This is the first analysis to show an algorithm which breaks the natural 1 − 1/e ‘barrier ’ in the unknown distribu ..."
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Cited by 34 (2 self)
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We consider the online bipartite matching problem in the unknown distribution input model. We show that the Ranking algorithm of [KVV90] achieves a competitive ratio of at least 0.653. This is the first analysis to show an algorithm which breaks the natural 1 − 1/e ‘barrier ’ in the unknown
Approximating discrete probability distributions with dependence trees
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 1968
"... A method is presented to approximate optimally an ndimensional discrete probability distribution by a product of secondorder distributions, or the distribution of the firstorder tree dependence. The problem is to find an optimum set of n1 first order dependence relationship among the n variables ..."
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Cited by 881 (0 self)
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variables. It is shown that the procedure derived in this paper yields an approximation of a minimum difference in information. It is further shown that when this procedure is applied to empirical observations from an unknown distribution of tree dependence, the procedure is the maximumlikelihood estimate
Distributed spacetimecoded protocols for exploiting cooperative diversity in wireless networks
 IEEE TRANS. INF. THEORY
, 2003
"... We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a m ..."
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Cited by 622 (5 self)
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We develop and analyze space–time coded cooperative diversity protocols for combating multipath fading across multiple protocol layers in a wireless network. The protocols exploit spatial diversity available among a collection of distributed terminals that relay messages for one another in such a
Games with Incomplete Information Played by 'Bayesian' Players, IIII
 MANAGEMENT SCIENCE
, 1967
"... The paper develops a new theory for the analysis of games with incomplete information where the players are uncertain about some important parameters of the game situation, such as the payoff functions, the strategies available to various players, the information other players have about the game, e ..."
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Cited by 787 (2 self)
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probability distributions derived from a certain "basic probability distribution " over the parameters unknown to the various players But later the theory is extended also to cases where the different players' subjective probability distributions fail to satisfy this consistency assumption
Nonparametric estimation of average treatment effects under exogeneity: a review
 REVIEW OF ECONOMICS AND STATISTICS
, 2004
"... Recently there has been a surge in econometric work focusing on estimating average treatment effects under various sets of assumptions. One strand of this literature has developed methods for estimating average treatment effects for a binary treatment under assumptions variously described as exogen ..."
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Cited by 630 (25 self)
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considered estimation and inference for average treatment effects under weaker assumptions than typical of the earlier literature by avoiding distributional and functionalform assumptions. Various methods of semiparametric estimation have been proposed, including estimating the unknown regression functions
Construction of Escherichia coli K12 inframe, singlegene knockout mutants: the Keio collection. Mol. Syst. Biol 2:2006.0008
, 2006
"... We have systematically made a set of precisely defined, singlegene deletions of all nonessential genes in Escherichia coli K12. Openreading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a onestep method for inactivation of chromosom ..."
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Cited by 714 (7 self)
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collection’—provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genomewide testing of mutational effects in a common strain background, E. coli K12 BW25113. We were unable to disrupt 303 genes, including 37 of unknown function, which
Consensus in the presence of partial synchrony
 JOURNAL OF THE ACM
, 1988
"... The concept of partial synchrony in a distributed system is introduced. Partial synchrony lies between the cases of a synchronous system and an asynchronous system. In a synchronous system, there is a known fixed upper bound A on the time required for a message to be sent from one processor to ano ..."
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Cited by 513 (18 self)
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The concept of partial synchrony in a distributed system is introduced. Partial synchrony lies between the cases of a synchronous system and an asynchronous system. In a synchronous system, there is a known fixed upper bound A on the time required for a message to be sent from one processor
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
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Cited by 726 (8 self)
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Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass
Results 1  10
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10,578