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Perturbation Analysis
"... PA addresses: ffl \Delta` ! 0: estimating the gradient dl(`) d` ; when l is differentiable in `; ffl \Delta` 6= 0: estimating changes due to a finite perturbation, i.e., l(` + \Delta`): In the former case, no perturbation is ever actually introduced into the system (or simulation), although the ..."
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Cited by 4 (0 self)
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the idea of a perturbation may be employed as a heuristic tool in preliminary analysis. To sort out the abundance of acronyms in the PA field, we provide a brief definition of each corresponding approach, along with a reference. Among gradient estimation techniques, by far the most wellknown
Stochastic Perturbation Theory
, 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
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Cited by 886 (35 self)
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. In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating
Perturbation Analysis and Malliavin Calculus
"... Using the Malliavin calculus, we give a unified treatment of the socalled perturbation analysis of dynamic systems. Several applications are also given. ..."
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Cited by 7 (3 self)
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Using the Malliavin calculus, we give a unified treatment of the socalled perturbation analysis of dynamic systems. Several applications are also given.
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 5350 (67 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
On Spectral Clustering: Analysis and an algorithm
 ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS
, 2001
"... Despite many empirical successes of spectral clustering methods  algorithms that cluster points using eigenvectors of matrices derived from the distances between the points  there are several unresolved issues. First, there is a wide variety of algorithms that use the eigenvectors in slightly ..."
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Cited by 1697 (13 self)
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in slightly different ways. Second, many of these algorithms have no proof that they will actually compute a reasonable clustering. In this paper, we present a simple spectral clustering algorithm that can be implemented using a few lines of Matlab. Using tools from matrix perturbation theory, we analyze
Pattern name Perturbation Analysis
"... Patterns are a tool that enables the collective knowledge of a particular community to be recorded and transmitted in an efficient manner. Initially developed in the field of architecture and later developed by software engineers [6], they have now been adopted by the complex systems modelling commu ..."
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, Perturbation Analysis, which describes the underlying framework used by several analytical and visualisation tools to quantify and explore the stability of dynamic systems. The format of this paper follows the outline specified in [15].
REFLECTIVE MODEL AND PERTURBATION ANALYSIS
, 2009
"... In this paper, we present a novel methodology for tracking performance evaluation. Considering the continuity of the image sequences in a video, we define a new measurement called tracking difficulty which incorporates the local sequence information among a small image sequence centered at each fram ..."
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perturbation analysis to the reflective model to examine how sensitive the tracking algorithm is to noise. Results on data sets are presented to show the effectiveness of our evaluation method.
Probabilistic Latent Semantic Analysis
 In Proc. of Uncertainty in Artificial Intelligence, UAI’99
, 1999
"... Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of twomode and cooccurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent Sema ..."
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Cited by 760 (9 self)
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Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of twomode and cooccurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent
Multivariable Feedback Control: Analysis
 span (B∗) und Basis B∗ = { ω1
, 2005
"... multiinput, multioutput feedback control design for linear systems using the paradigms, theory, and tools of robust control that have arisen during the past two decades. The book is aimed at graduate students and practicing engineers who have a basic knowledge of classical control design and st ..."
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Cited by 529 (24 self)
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multiinput, multioutput feedback control design for linear systems using the paradigms, theory, and tools of robust control that have arisen during the past two decades. The book is aimed at graduate students and practicing engineers who have a basic knowledge of classical control design and statespace control theory for linear systems. A basic knowledge of matrix theory and linear algebra is required to appreciate and digest the material offered. This edition is a revised and expanded version of the first edition, which was published in 1996. The size of the
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 630 (57 self)
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to the database. To protect privacy, the true answer is perturbed by the addition of random noise generated according to a carefully chosen distribution, and this response, the true answer plus noise, is returned to the user. Previous work focused on the case of noisy sums, in which f =P i g(xi), where xi denotes
Results 1  10
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