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23,093
Onevariable word equations in linear time
, 2013
"... Abstract. In this paper we consider word equations with one variable (and arbitrary many occurrences of it). A recent technique of recompression, which is applicable to general word equations, is shown to be suitable also in this case. While in general case the recompression is nondeterministic it ..."
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Cited by 4 (3 self)
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Abstract. In this paper we consider word equations with one variable (and arbitrary many occurrences of it). A recent technique of recompression, which is applicable to general word equations, is shown to be suitable also in this case. While in general case the recompression is non
Training Linear SVMs in Linear Time
, 2006
"... Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like text classification, wordsense disambiguation, and drug design. These applications involve a large number of examples n ..."
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Cited by 549 (6 self)
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Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like text classification, wordsense disambiguation, and drug design. These applications involve a large number of examples n
Longitudinal data analysis using generalized linear models”.
 Biometrika,
, 1986
"... SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence. The estimating ..."
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Cited by 1526 (8 self)
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SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence
Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences
 ACOUSTICS, SPEECH AND SIGNAL PROCESSING, IEEE TRANSACTIONS ON
, 1980
"... Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllableoriented continuous speech recognition system. The vocabulary included many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain phonetically ..."
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Cited by 1120 (2 self)
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phonetically significant acoustic information in the face of syntactic and duration variations. For each ~ arameter set (based on a melfrequency cepstrum, a linear frequency cepstrum, a linear prediction cepstrum, a linear prediction spectrum, or a set of reflection coefficients), word templates were
Strongly Elliptic Systems and Boundary Integral Equations
, 2000
"... Partial differential equations provide mathematical models of many important problems in the physical sciences and engineering. This book treats one class of such equations, concentrating on methods involving the use of surface potentials. It provides the first detailed exposition of the mathematic ..."
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Cited by 501 (0 self)
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Partial differential equations provide mathematical models of many important problems in the physical sciences and engineering. This book treats one class of such equations, concentrating on methods involving the use of surface potentials. It provides the first detailed exposition
A Signal Processing Approach To Fair Surface Design
, 1995
"... In this paper we describe a new tool for interactive freeform fair surface design. By generalizing classical discrete Fourier analysis to twodimensional discrete surface signals  functions defined on polyhedral surfaces of arbitrary topology , we reduce the problem of surface smoothing, or fai ..."
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Cited by 654 (15 self)
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, or fairing, to lowpass filtering. We describe a very simple surface signal lowpass filter algorithm that applies to surfaces of arbitrary topology. As opposed to other existing optimizationbased fairing methods, which are computationally more expensive, this is a linear time and space complexity algorithm
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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of alternatives, accounting for the linear slowing of reaction time as a function of the log of the number of alternatives (Hick’s law) and explains a complex pattern of visual and contextual priming effects in visual word identification. Perceptual Choice 2 When an experience presents itself to the senses
Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems
 IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING
, 2007
"... Many problems in signal processing and statistical inference involve finding sparse solutions to underdetermined, or illconditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined with a spa ..."
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Cited by 539 (17 self)
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Many problems in signal processing and statistical inference involve finding sparse solutions to underdetermined, or illconditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined with a
An Introduction to the Kalman Filter
 UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
, 1995
"... In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area o ..."
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Cited by 1146 (13 self)
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In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area
Convex Analysis
, 1970
"... In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a lo ..."
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Cited by 5411 (68 self)
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In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a
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