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SPARSKIT: a basic tool kit for sparse matrix computations  Version 2
, 1994
"... . This paper presents the main features of a tool package for manipulating and working with sparse matrices. One of the goals of the package is to provide basic tools to facilitate exchange of software and data between researchers in sparse matrix computations. Our starting point is the Harwell/Boei ..."
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Cited by 317 (22 self)
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. This paper presents the main features of a tool package for manipulating and working with sparse matrices. One of the goals of the package is to provide basic tools to facilitate exchange of software and data between researchers in sparse matrix computations. Our starting point is the Harwell
The University of Florida sparse matrix collection
 NA DIGEST
, 1997
"... The University of Florida Sparse Matrix Collection is a large, widely available, and actively growing set of sparse matrices that arise in real applications. Its matrices cover a wide spectrum of problem domains, both those arising from problems with underlying 2D or 3D geometry (structural enginee ..."
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Cited by 538 (19 self)
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The University of Florida Sparse Matrix Collection is a large, widely available, and actively growing set of sparse matrices that arise in real applications. Its matrices cover a wide spectrum of problem domains, both those arising from problems with underlying 2D or 3D geometry (structural
Matrix computations
, 1989
"... With increasing complexity of the data impractical to use a single feature to constituent images. In this paper we describ will automatically select the appropriate im are relevant and efficacious for classif requiring modifications to the feature extra the classification algorithm. We first descr d ..."
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Cited by 4 (0 self)
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With increasing complexity of the data impractical to use a single feature to constituent images. In this paper we describ will automatically select the appropriate im are relevant and efficacious for classif requiring modifications to the feature extra the classification algorithm. We first descr designing class distinctive dictionaries us learning technique, which yields class spec and a linear classifier parameter. Th information theoretic measures to ob informative feature relevant to a test image feature to obtain final classification results. of the features classifying the query algorithm chooses the correct feature in 88.9 Index Terms—dictionary learning sparse representation, conditional en
Algorithms for Nonnegative Matrix Factorization
 In NIPS
, 2001
"... Nonnegative matrix factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. Two different multiplicative algorithms for NMF are analyzed. They differ only slightly in the multiplicative factor used in the update rules. One algorithm can be shown to minim ..."
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Cited by 1230 (5 self)
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Nonnegative matrix factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. Two different multiplicative algorithms for NMF are analyzed. They differ only slightly in the multiplicative factor used in the update rules. One algorithm can be shown
A Singular Value Thresholding Algorithm for Matrix Completion
, 2008
"... This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task of reco ..."
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Cited by 539 (20 self)
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This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood as the convex relaxation of a rank minimization problem, and arises in many important applications as in the task
Learning the Kernel Matrix with SemiDefinite Programming
, 2002
"... Kernelbased 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 ..."
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Cited by 780 (22 self)
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is contained in the socalled 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 spaceclassical model selection
Randomized Matrix Computations
, 2012
"... We propose new effective randomized algorithms for some fundamental matrix computations such as preconditioning of an ill conditioned matrix that has a small numerical nullity or rank, its 2by2 block triangulation, numerical stabilization of Gaussian elimination with no pivoting, and approximation ..."
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Cited by 52 (6 self)
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We propose new effective randomized algorithms for some fundamental matrix computations such as preconditioning of an ill conditioned matrix that has a small numerical nullity or rank, its 2by2 block triangulation, numerical stabilization of Gaussian elimination with no pivoting
Simulating Physics with Computers
 SIAM Journal on Computing
, 1982
"... A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. ..."
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Cited by 601 (1 self)
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A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration
Formalising trust as a computational concept
, 1994
"... Trust is a judgement of unquestionable utility — as humans we use it every day of our lives. However, trust has suffered from an imperfect understanding, a plethora of definitions, and informal use in the literature and in everyday life. It is common to say “I trust you, ” but what does that mean? T ..."
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Cited by 518 (5 self)
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Trust is a judgement of unquestionable utility — as humans we use it every day of our lives. However, trust has suffered from an imperfect understanding, a plethora of definitions, and informal use in the literature and in everyday life. It is common to say “I trust you, ” but what does that mean? This thesis provides a clarification of trust. We present a formalism for trust which provides us with a tool for precise discussion. The formalism is implementable: it can be embedded in an artificial agent, enabling the agent to make trustbased decisions. Its applicability in the domain of Distributed Artificial Intelligence (DAI) is raised. The thesis presents a testbed populated by simple trusting agents which substantiates the utility of the formalism. The formalism provides a step in the direction of a proper understanding and definition of human trust. A contribution of the thesis is its detailed exploration of the possibilities of future work in the area. Summary 1. Overview This thesis presents an overview of trust as a social phenomenon and discusses it formally. It argues that trust is: • A means for understanding and adapting to the complexity of the environment. • A means of providing added robustness to independent agents. • A useful judgement in the light of experience of the behaviour of others. • Applicable to inanimate others. The thesis argues these points from the point of view of artificial agents. Trust in an artificial agent is a means of providing an additional tool for the consideration of other agents and the environment in which it exists. Moreover, a formalisation of trust enables the embedding of the concept into an artificial agent. This has been done, and is documented in the thesis. 2. Exposition There are places in the thesis where it is necessary to give a broad outline before going deeper. In consequence it may seem that the subject is not receiving a thorough treatment, or that too much is being discussed at one time! (This is particularly apparent in the first and second chapters.) To present a thorough understanding of trust, we have proceeded breadth first in the introductory chapters. Chapter 3 expands, depth first, presenting critical views of established researchers.
Algorithms for Quantum Computation: Discrete Logarithms and Factoring
, 1994
"... A computer is generally considered to be a universal computational device; i.e., it is believed able to simulate any physical computational device with a increase in computation time of at most a polynomial factor. It is not clear whether this is still true when quantum mechanics is taken into consi ..."
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Cited by 1103 (7 self)
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A computer is generally considered to be a universal computational device; i.e., it is believed able to simulate any physical computational device with a increase in computation time of at most a polynomial factor. It is not clear whether this is still true when quantum mechanics is taken
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