Results 271 to 280 of about 35,609 (308)

From the Subspace Methods to the Mutual Subspace Method

2010
The Subspace Method [25, 21] is a classic method of pattern recognition, and has been applied to various tasks. The Mutual Subspace Method [19] is an extension of the Subspace Methods, in which canonical angles (principal angles) between two subspaces are used to define similarity between two patterns (or two sets of patterns). The method is applied to
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A Krylov Subspace Method for Information Retrieval

SIAM Journal on Matrix Analysis and Applications, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Katarina Blom, Axel Ruhe
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Spectral Variants of Krylov Subspace Methods

Numerical Algorithms, 2002
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Brígida Molina, Marcos Raydan
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From Subspace to Submanifold Methods

Procedings of the British Machine Vision Conference 2004, 2004
Twenty years ago it was not obvious that subspace approximations would be such a successful representation for faces and other phenomena whose measurement-space manifolds exhibit clear nonlinearities. Now PCA is ubiquitous in computer vision and, although its globally linear view of the data manifold can be a liability as systems scale up, it is not ...
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Admissible subspaces and the subspace iteration method

BIT Numerical Mathematics
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Projection Methods in Krylov Subspaces

Journal of Mathematical Sciences, 2019
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An enhanced subspace method for face recognition

Pattern Recognition Letters, 2006
In this paper we introduce a new face recognition approach based on the representation of each individual by several lower dimensional subspaces obtained by an unsupervised clustering of different poses: this provides a higher robustness to face variations than traditional subspace approaches. A set of subspaces is created for each individual, starting
Annalisa Franco, Alessandra Lumini, Dario Maio, Loris Nanni   +3 more
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Consistency and relative efficiency of subspace methods

Automatica, 1994
Some identification procedures for linear stochastic systems are analyzed and compared. The systems are assumed to be stable. Strictly, minimum phase and having a known order. The first algorithm was proposed by Akaike (1976), the second one was presented by Larimore (1983).
Deistler, Manfred, Peternell, K., Scherrer, Wolfgang   +2 more
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Error-Minimizing Krylov Subspace Methods

SIAM Journal on Scientific Computing, 1994
This paper first introduces generalized conjugate gradient methods which specialize to error minimizing procedures as well as to residual minimizing methods. General minimum error methods are then introduced, and the two method classes are compared.
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A Brief History of the Subspace Methods

2011
I hope to start from one question. "Is the eigenface[1] a subspace method?" Answer is weakly YES and strongly NO. In wide meaning in Subspace method of pattern recognition is that uses subspace. In this meaning the answer is YES. However in narrow meaning the term "Subspace method" means pattern recognition techniques that represent class featuring ...
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