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A New Method for Solving Hard Satisfiability Problems
 AAAI
, 1992
"... We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approac ..."
Abstract

Cited by 730 (21 self)
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discussed. GSAT is best viewed as a modelfinding procedure. Its good performance suggests that it may be advantageous to reformulate reasoning tasks that have traditionally been viewed as theoremproving problems as modelfinding tasks.
An analysis of transformations
 Journal of the Royal Statistical Society. Series B (Methodological
, 1964
"... In the analysis of data it is often assumed that observations y,, y,,...,y, are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal, homoscedasti ..."
Abstract

Cited by 1067 (3 self)
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, homoscedasticity and additivity to the transformation are separated. The relation of the present methods to earlier procedures for finding transformations is discussed. The methods are illustrated with examples. 1.
A gentle tutorial on the EM algorithm and its application to parameter estimation for gaussian mixture and hidden markov models
, 1997
"... We describe the maximumlikelihood parameter estimation problem and how the Expectationform of the EM algorithm as it is often given in the literature. We then develop the EM parameter estimation procedure for two applications: 1) finding the parameters of a mixture of Gaussian densities, and 2) fi ..."
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Cited by 693 (4 self)
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We describe the maximumlikelihood parameter estimation problem and how the Expectationform of the EM algorithm as it is often given in the literature. We then develop the EM parameter estimation procedure for two applications: 1) finding the parameters of a mixture of Gaussian densities, and 2
Pig Latin: A NotSoForeign Language for Data Processing
"... There is a growing need for adhoc analysis of extremely large data sets, especially at internet companies where innovation critically depends on being able to analyze terabytes of data collected every day. Parallel database products, e.g., Teradata, offer a solution, but are usually prohibitively e ..."
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Cited by 607 (13 self)
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expensive at this scale. Besides, many of the people who analyze this data are entrenched procedural programmers, who find the declarative, SQL style to be unnatural. The success of the more procedural mapreduce programming model, and its associated scalable implementations on commodity hardware
The Skill Content of Recent Technological Change: An Empirical Exploration
, 2000
"... Recent empirical and case study evidence documents a strong association between the adoption of computers and increased use of college educated or nonproduction workers. With few exceptions, the conceptual link explaining how computer technology complements skilled labor or substitutes for unskille ..."
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Cited by 643 (28 self)
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for unskilled labor is less well developed. In this paper, we apply an understanding of what computers do – the execution of procedural or rulesbased logic – to develop a simple model of how the widespread adoption of computers in the workplace might alter workplace skill demands. An essential contention
Policy Rules for Inflation Targeting
, 1998
"... Policy rules that are consistent with ination targeting are examined in a small macroeconometric model of the US economy. We compare the properties and outcomes of explicit instrument rules as well as targeting rules. The latter, which imply implicit instrument rules, may be closer to actual operati ..."
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Cited by 404 (47 self)
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operating procedures of inflationtargeting central banks. We find that ination forecasts are central for good policy rules under inflation targeting. Some simple instrument and targeting rules do remarkably well relative to the optimal rule; others, including some that are often used as representing
Nearoptimal sensor placements in gaussian processes
 In ICML
, 2005
"... When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to address this task, for example, geometry or disk models, placing sensors at the points of highest entropy (variance) in t ..."
Abstract

Cited by 342 (34 self)
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) in the GP model, and A, D, or Eoptimal design. In this paper, we tackle the combinatorial optimization problem of maximizing the mutual information between the chosen locations and the locations which are not selected. We prove that the problem of finding the configuration that maximizes mutual
Data privacy through optimal kanonymization
 In ICDE
, 2005
"... Data deidentification reconciles the demand for release of data for research purposes and the demand for privacy from individuals. This paper proposes and evaluates an optimization algorithm for the powerful deidentification procedure known as kanonymization. A kanonymized dataset has the proper ..."
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Cited by 344 (3 self)
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Data deidentification reconciles the demand for release of data for research purposes and the demand for privacy from individuals. This paper proposes and evaluates an optimization algorithm for the powerful deidentification procedure known as kanonymization. A kanonymized dataset has
GSAT: A new method for solving hard satisfiability problems
, 1992
"... We introduce a greedy local search procedure called GSAT for solving propositional satis ability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approach ..."
Abstract

Cited by 9 (2 self)
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discussed. GSAT is best viewed as a modelfinding procedure. Its good performance suggests that it may beadvantageous to reformulate reasoning tasks that have traditionally been viewed as theoremproving problems as modelfinding tasks.
A New Met is Y s
"... Abstract We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more tradition ..."
Abstract
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are also discussed. GSAT is best viewed as a modelfinding procedure. Its good performance suggests that it may be advantageous to reformulate reasoning tasks that have traditionally been viewed as theoremproving problems as modelfinding tasks.
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