Results 1 - 10 of 19,403

Stochastic Perturbation Theory

by G. W. Stewart , 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a first-order perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
Abstract - Cited by 907 (36 self) - Add to MetaCart
. In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a first-order perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating

Learning the Kernel Matrix with Semi-Definite Programming

by Gert R. G. Lanckriet, Nello Cristianini, Laurent El Ghaoui, Peter Bartlett, Michael I. Jordan , 2002
"... Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information ..."
Abstract - Cited by 775 (21 self) - Add to MetaCart
is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space---classical model selection

Discovery of Grounded Theory

by Barney G. Glaser, Judith Holton , 1967
"... Abstract: This paper outlines my concerns with Qualitative Data Analysis ’ (QDA) numerous remodelings of Grounded Theory (GT) and the subsequent eroding impact. I cite several examples of the erosion and summarize essential elements of classic GT methodology. It is hoped that the article will clarif ..."
Abstract - Cited by 2637 (13 self) - Add to MetaCart
Abstract: This paper outlines my concerns with Qualitative Data Analysis ’ (QDA) numerous remodelings of Grounded Theory (GT) and the subsequent eroding impact. I cite several examples of the erosion and summarize essential elements of classic GT methodology. It is hoped that the article

Quantum complexity theory

by Ethan Bernstein, Umesh Vazirani - in Proc. 25th Annual ACM Symposium on Theory of Computing, ACM , 1993
"... Abstract. In this paper we study quantum computation from a complexity theoretic viewpoint. Our first result is the existence of an efficient universal quantum Turing machine in Deutsch’s model of a quantum Turing machine (QTM) [Proc. Roy. Soc. London Ser. A, 400 (1985), pp. 97–117]. This constructi ..."
Abstract - Cited by 574 (5 self) - Add to MetaCart
Abstract. In this paper we study quantum computation from a complexity theoretic viewpoint. Our first result is the existence of an efficient universal quantum Turing machine in Deutsch’s model of a quantum Turing machine (QTM) [Proc. Roy. Soc. London Ser. A, 400 (1985), pp. 97

A General Theory of Equilibrium Selection in Games.

by References Harsanyi , J C Seleten , R , 1988
"... Abstract This paper presents a Downsian model of political competition in which parties have incomplete but richer information than voters on policy effects. Each party can observe a private signal of the policy effects, while voters cannot. In this setting, voters infer the policy effects from the ..."
Abstract - Cited by 734 (4 self) - Add to MetaCart
of the Median Voter Theorem in the classical Downsian model. Our equilibrium analysis suggests similarity between the set of WPBEs in this model and the set of uniformly perfect equilibria of Harsanyi and Selten (1988) in the model with completely informed parties which we studied in a previous paper

On Spectral Clustering: Analysis and an algorithm

by Andrew Y. Ng, Michael I. Jordan, Yair Weiss - 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 ..."
Abstract - Cited by 1713 (13 self) - Add to MetaCart
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

Multivariable Feedback Control: Analysis

by Sigurd Skogestad, Ian Postlethwaite - span (B∗) und Basis B∗ = { ω1 , 2005
"... multi-input, multi-output feed-back control design for linear systems using the paradigms, theory, and tools of robust con-trol 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 con-trol design and st ..."
Abstract - Cited by 564 (24 self) - Add to MetaCart
multi-input, multi-output feed-back control design for linear systems using the paradigms, theory, and tools of robust con-trol 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 con-trol design

The geometry of algorithms with orthogonality constraints

by Alan Edelman, Tomás A. Arias, Steven T. Smith - SIAM J. MATRIX ANAL. APPL , 1998
"... In this paper we develop new Newton and conjugate gradient algorithms on the Grassmann and Stiefel manifolds. These manifolds represent the constraints that arise in such areas as the symmetric eigenvalue problem, nonlinear eigenvalue problems, electronic structures computations, and signal proces ..."
Abstract - Cited by 640 (1 self) - Add to MetaCart
of previously unrelated algorithms. It is our hope that developers of new algorithms and perturbation theories will benefit from the theory, methods, and examples in this paper.

Decoding by Linear Programming

by Emmanuel J. Candès, Terence Tao , 2004
"... This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector f ∈ Rn from corrupted measurements y = Af + e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible to rec ..."
Abstract - Cited by 1399 (16 self) - Add to MetaCart
This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector f ∈ Rn from corrupted measurements y = Af + e. Here, A is an m by n (coding) matrix and e is an arbitrary and unknown vector of errors. Is it possible

A Data Locality Optimizing Algorithm

by Michael E. Wolf, Monica S. Lam , 1991
"... This paper proposes an algorithm that improves the locality of a loop nest by transforming the code via interchange, reversal, skewing and tiling. The loop transformation algorithm is based on two concepts: a mathematical formulation of reuse and locality, and a loop transformation theory that unifi ..."
Abstract - Cited by 804 (16 self) - Add to MetaCart
This paper proposes an algorithm that improves the locality of a loop nest by transforming the code via interchange, reversal, skewing and tiling. The loop transformation algorithm is based on two concepts: a mathematical formulation of reuse and locality, and a loop transformation theory
Results 1 - 10 of 19,403