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Verifiable Random Functions from Standard Assumptions
, 2015
"... The question whether there exist verifiable random functions with exponentialsized input space and full adaptive security based on a noninteractive, constantsize assumption is a longstanding open problem. We construct the first verifiable random functions which achieve all these properties simul ..."
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The question whether there exist verifiable random functions with exponentialsized input space and full adaptive security based on a noninteractive, constantsize assumption is a longstanding open problem. We construct the first verifiable random functions which achieve all these properties
Random Early Detection Gateways for Congestion Avoidance.
 IEEELACM Transactions on Networking,
, 1993
"... AbstractThis paper presents Random Early Detection (RED) gateways for congestion avoidance in packetswitched networks. The gateway detects incipient congestion by computing the average queue size. The gateway could notify connections of congestion either by dropping packets arriving at the gatewa ..."
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Cited by 2716 (31 self)
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at the gateway, and of notifying connections of incipient congestion, is based on the assumption that it will continue to be useful to have queues at the gateway where traffic from a number of connections is multiplexed together with FIFO scheduling. Not only is FIFO scheduling useful for sharing delay among
Experimental Estimates of Education Production Functions
 Princeton University, Industrial Relations Section Working Paper No. 379
, 1997
"... This paper analyzes data on 11,600 students and their teachers who were randomly assigned to different size classes from kindergarten through third grade. Statistical methods are used to adjust for nonrandom attrition and transitions between classes. The main conclusions are (1) on average, performa ..."
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Cited by 529 (19 self)
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This paper analyzes data on 11,600 students and their teachers who were randomly assigned to different size classes from kindergarten through third grade. Statistical methods are used to adjust for nonrandom attrition and transitions between classes. The main conclusions are (1) on average
Fast and robust fixedpoint algorithms for independent component analysis
 IEEE TRANS. NEURAL NETW
, 1999
"... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s informat ..."
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Cited by 884 (34 self)
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Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s
A logic of authentication
 ACM TRANSACTIONS ON COMPUTER SYSTEMS
, 1990
"... Questions of belief are essential in analyzing protocols for the authentication of principals in distributed computing systems. In this paper we motivate, set out, and exemplify a logic specifically designed for this analysis; we show how various protocols differ subtly with respect to the required ..."
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Cited by 1332 (22 self)
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to suggest improvements to the protocols. The reasoning about some protocols has been mechanically verified. This paper starts with an informal account of the problem, goes on to explain the formalism to be used, and gives examples of its application to protocols from the literature, both with shared
Robust face recognition via sparse representation
 IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 2008
"... We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse signa ..."
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Cited by 936 (40 self)
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We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse
Calibrating noise to sensitivity in private data analysis
 In Proceedings of the 3rd Theory of Cryptography Conference
, 2006
"... Abstract. We continue a line of research initiated in [10, 11] on privacypreserving statistical databases. Consider a trusted server that holds a database of sensitive information. Given a query function f mapping databases to reals, the socalled true answer is the result of applying f to the datab ..."
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Cited by 649 (60 self)
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the ith row of the database and g maps database rows to [0, 1]. We extend the study to general functions f, proving that privacy can be preserved by calibrating the standard deviation of the noise according to the sensitivity of the function f. Roughly speaking, this is the amount that any single
On the time course of perceptual choice: the leaky competing accumulator model
 PSYCHOLOGICAL REVIEW
, 2001
"... The time course of perceptual choice is discussed in a model based on gradual and stochastic accumulation of information in nonlinear decision units with leakage (or decay of activation) and competition through lateral inhibition. In special cases, the model becomes equivalent to a classical diffus ..."
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Cited by 480 (19 self)
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diffusion process, but leakage and mutual inhibition work together to address several challenges to existing diffusion, randomwalk, and accumulator models. The model provides a good account of data from choice tasks using both timecontrolled (e.g., deadline or response signal) and standard reaction time
Monetary Policy Rules Based on RealTime Data
 BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM FINANCE AND ECONOMICS DISCUSSION PAPER SERIES
, 1997
"... In recent years, simple policy rules have received attention as a means to a more transparent and effective monetary policy. Often, however, the analysis is based on unrealistic assumptions about the timeliness of data availability. This permits rule specifications that are not operational and ignor ..."
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Cited by 431 (18 self)
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quite large with a standard deviation exceeding that of the quarterly change of the federal funds rate. Further, I show that estimated policy reaction functions obtained using the ex post revised data can yield misleading descriptions of historical policy. Using Federal Reserve sta forecasts I show
Randomized Experiments from Nonrandom Selection in the U.S. House Elections
 Journal of Econometrics
, 2008
"... This paper establishes the relatively weak conditions under which causal inferences from a regressiondiscontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a discont ..."
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Cited by 377 (17 self)
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This paper establishes the relatively weak conditions under which causal inferences from a regressiondiscontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a
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