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Empirical tests of the Gradual Learning Algorithm
 LINGUISTIC INQUIRY 32.45–86
, 2001
"... The Gradual Learning Algorithm (Boersma 1997) is a constraint ranking algorithm for learning Optimalitytheoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and Smol ..."
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Cited by 378 (37 self)
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and Smolensky (1993, 1996, 1998, 2000), which initiated the learnability research program for Optimality Theory. We argue that the Gradual Learning Algorithm has a number of special advantages: it can learn free variation, deal effectively with noisy learning data, and account for gradient wellformedness
Understanding FaultTolerant Distributed Systems
 COMMUNICATIONS OF THE ACM
, 1993
"... We propose a small number of basic concepts that can be used to explain the architecture of faulttolerant distributed systems and we discuss a list of architectural issues that we find useful to consider when designing or examining such systems. For each issue we present known solutions and design ..."
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Cited by 374 (23 self)
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We propose a small number of basic concepts that can be used to explain the architecture of faulttolerant distributed systems and we discuss a list of architectural issues that we find useful to consider when designing or examining such systems. For each issue we present known solutions and design
Testing Juntas
, 2010
"... A function on n variables is called a kjunta if it depends on at most k of its variables. The problem of testing whether a function is a kjunta or is “far” from being a kjunta is a central problem in property testing and is closely related to the problem of learning highdimensional data. In this ..."
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. In this note, we give an informal presentation of three recent algorithms for testing juntas efficiently.
Testing Juntas
, 2002
"... We show that a Boolean function over n Boolean variables can be tested for the property of depending on only k of them, using a number of queries that depends only on k and the approximation parameter . We present two tests, both nonadaptive, that require a number of queries that is polynomial k an ..."
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Cited by 57 (12 self)
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and linear in . The first test is stronger in that it has a 1sided error, while the second test has a more compact analysis. We also present an adaptive version and a 2sided error version of the first test, that have a somewhat better query complexity than the other algorithms...
Requirements for Internet Hosts  Application and Support
 STD 3, RFC 1123, IETF
, 1989
"... This RFC is an official specification for the Internet community. It incorporates by reference, amends, corrects, and supplements the primary protocol standards documents relating to hosts. Distribution of this document is unlimited. Summary This RFC is one of a pair that defines and discusses the r ..."
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Cited by 319 (1 self)
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This RFC is an official specification for the Internet community. It incorporates by reference, amends, corrects, and supplements the primary protocol standards documents relating to hosts. Distribution of this document is unlimited. Summary This RFC is one of a pair that defines and discusses
Network Centric Warfare: Developing and Leveraging Information Superiority
 Command and Control Research Program (CCRP), US DoD
, 2000
"... the mission of improving DoD’s understanding of the national security implications of the Information Age. Focusing upon improving both the state of the art and the state of the practice of command and control, the CCRP helps DoD take full advantage of the opportunities afforded by emerging technolo ..."
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Cited by 308 (5 self)
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the mission of improving DoD’s understanding of the national security implications of the Information Age. Focusing upon improving both the state of the art and the state of the practice of command and control, the CCRP helps DoD take full advantage of the opportunities afforded by emerging technologies. The CCRP pursues a broad program of research and analysis in information superiority, information operations, command and control theory, and associated operational concepts that enable us to leverage shared awareness to improve the effectiveness and efficiency of assigned missions. An important aspect of the CCRP program is its ability to serve as a bridge between the operational, technical, analytical, and educational communities. The CCRP provides leadership for the command and control research community by: n n
DistributionFree Distribution Regression
"... ‘Distribution regression ’ refers to the situation where a response Y depends on a covariate P where P is a probability distribution. The model is Y = f(P) + µ where f is an unknown regression function and µ is a random error. Typically, we do not observe P directly, but rather, we observe a samp ..."
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sample from P. In this paper we develop theory and methods for distributionfree versions of distribution regression. This means that we do not make strong distributional assumptions about the error term µ and covariate P. We prove that when the effective dimension is small enough (as measured
DistributionFree Distribution Regression
"... ‘Distribution regression ’ refers to the situation where a response Y depends on a covariate P where P is a probability distribution. The model is Y = f(P) + µ where f is an unknown regression function and µ is a random error. Typically, we do not observe P directly, but rather, we observe a samp ..."
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sample from P. In this paper we develop theory and methods for distributionfree versions of distribution regression. This means that we do not make strong distributional assumptions about the error term µ and covariate P. We prove that when the effective dimension is small enough (as measured
Distributionfree Discriminant Analysis
, 1996
"... This report describes our experience in implementing a nonparametric (distribution free) discriminant analysis module for use in a wide range of pattern recognition problems. Issues discussed include performance results on both real and simulated data sets, comparisons to other methods, and the com ..."
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Cited by 1 (0 self)
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This report describes our experience in implementing a nonparametric (distribution free) discriminant analysis module for use in a wide range of pattern recognition problems. Issues discussed include performance results on both real and simulated data sets, comparisons to other methods
DistributionFree Testing for Monomials with a Sublinear Number of Queries
, 2011
"... We consider the problem of distributionfree testing of the class of monotone monomials and the class of monomials over n variables. While there are very efficient testers for a variety of classes of functions when the underlying distribution is uniform, designing distributionfree testers (which ..."
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Cited by 2 (0 self)
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We consider the problem of distributionfree testing of the class of monotone monomials and the class of monomials over n variables. While there are very efficient testers for a variety of classes of functions when the underlying distribution is uniform, designing distributionfree testers (which
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549,337