19 search results - page 2 / 4 » Independent Subspace Analysis Is Unique, Given Irreducibilit... |
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
ICPR
2004
IEEE
15 years 10 months ago
2004
IEEE
In the past decade or so, subspace methods have been largely used in face recognition ? generally with quite success. Subspace approaches, however, generally assume the training d...
TNN
1998
14 years 9 months ago
1998
— In this paper, we perform a complete asymptotic performance analysis of the stochastic approximation algorithm (denoted subspace network learning algorithm) derived from Oja’...
SIAMSC
2010
14 years 7 months ago
2010
The shift-invert Arnoldi method is employed to generate an orthonormal basis from the Krylov subspace corresponding to a real Toeplitz matrix and an initial vector. The vectors and...
STOC
2006
ACM
15 years 9 months ago
2006
ACM
We present the first randomized polynomial-time simplex algorithm for linear programming. Like the other known polynomial-time algorithms for linear programming, its running time ...