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, 2011
"... • Let Y (x) be a random variable such that: Y (x) = 1 P (Y (x) = 1) = F (x) 0 P (Y (x) = 0) = 1 F (x) where F (x) is an unknown distribution function. • Objective: given ↵ estimate the ↵ quantile of F (x), xa = F 1(↵) with observations distributed like Y (x) where the choice of x is under cont ..."
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• Let Y (x) be a random variable such that: Y (x) = 1 P (Y (x) = 1) = F (x) 0 P (Y (x) = 0) = 1 F (x) where F (x) is an unknown distribution function. • Objective: given ↵ estimate the ↵ quantile of F (x), xa = F 1(↵) with observations distributed like Y (x) where the choice of x is under control.
Worstcase equilibria
 IN PROCEEDINGS OF THE 16TH ANNUAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE
, 1999
"... In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a ver ..."
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Cited by 847 (17 self)
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In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a
Detectability of Discrete Event Systems
"... In this paper, we investigate the detectability problem in discrete event systems. We assume that we do not know initially which state the system is in. The problem is to determine the current and subsequent states of the system based on a sequence of observation. The observation includes partial ev ..."
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Cited by 806 (14 self)
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event observation and/or partial state observation, which leads to four possible cases. We further define four types of detectabilities: strong detectability, (weak) detectability, strong periodic detectability, and (weak) periodic detectability. We derive necessary and sufficient conditions
Impossibility of distributed consensus with one faulty process
, 1983
"... The consensus problem involves an asynchronous system of proceses, some of which may be unreliable. The problem is for the rcliablc processes to agree on a bbary value. h this paper, it is shown that every protocol for this problem has the possibility of nontermination, even with only otre faulty p ..."
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Cited by 1721 (28 self)
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The consensus problem involves an asynchronous system of proceses, some of which may be unreliable. The problem is for the rcliablc processes to agree on a bbary value. h this paper, it is shown that every protocol for this problem has the possibility of nontermination, even with only otre faulty
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
, 2002
"... We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language senten ..."
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Cited by 508 (30 self)
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We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language
Estimation and Inference in Econometrics
, 1993
"... The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas o ..."
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Cited by 1204 (4 self)
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The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas
Maximum Likelihood Linear Transformations for HMMBased Speech Recognition
 COMPUTER SPEECH AND LANGUAGE
, 1998
"... This paper examines the application of linear transformations for speaker and environmental adaptation in an HMMbased speech recognition system. In particular, transformations that are trained in a maximum likelihood sense on adaptation data are investigated. Other than in the form of a simple bias ..."
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Cited by 570 (68 self)
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bias, strict linear featurespace transformations are inappropriate in this case. Hence, only modelbased linear transforms are considered. The paper compares the two possible forms of modelbased transforms: (i) unconstrained, where any combination of mean and variance transform may be used, and (ii
ProofCarrying Code
, 1997
"... This paper describes proofcarrying code (PCC), a mechanism by which a host system can determine with certainty that it is safe to execute a program supplied (possibly in binary form) by an untrusted source. For this to be possible, the untrusted code producer must supply with the code a safety proo ..."
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Cited by 1240 (27 self)
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This paper describes proofcarrying code (PCC), a mechanism by which a host system can determine with certainty that it is safe to execute a program supplied (possibly in binary form) by an untrusted source. For this to be possible, the untrusted code producer must supply with the code a safety
Planning and acting in partially observable stochastic domains
 ARTIFICIAL INTELLIGENCE
, 1998
"... In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains. We begin by introducing the theory of Markov decision processes (mdps) and partially observable mdps (pomdps). We then outline a novel algorithm ..."
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Cited by 1095 (38 self)
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for solving pomdps offline and show how, in some cases, a finitememory controller can be extracted from the solution to a pomdp. We conclude with a discussion of how our approach relates to previous work, the complexity of finding exact solutions to pomdps, and of some possibilities for finding approximate
Local grayvalue invariants for image retrieval
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1997
"... Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows for efficie ..."
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Cited by 548 (27 self)
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Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows
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