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TNN
2010
216views Management» more  TNN 2010»
15 years 1 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
ICASSP
2011
IEEE
14 years 10 months ago
Approximation of pattern transformation manifolds with parametric dictionaries
The construction of low-dimensional models explaining highdimensional signal observations provides concise and efficient data representations. In this paper, we focus on pattern ...
Elif Vural, Pascal Frossard
NIPS
1998
15 years 7 months ago
A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations
There has been much recent work on measuring image statistics and on learning probability distributions on images. We observe that the mapping from images to statistics is many-to...
James M. Coughlan, Alan L. Yuille
GD
2006
Springer
15 years 10 months ago
Eigensolver Methods for Progressive Multidimensional Scaling of Large Data
We present a novel sampling-based approximation technique for classical multidimensional scaling that yields an extremely fast layout algorithm suitable even for very large graphs....
Ulrik Brandes, Christian Pich
IPPS
2006
IEEE
16 years 16 days ago
On the performance of parallel normalized explicit preconditioned conjugate gradient type methods
A new class of parallel normalized preconditioned conjugate gradient type methods in conjunction with normalized approximate inverses algorithms, based on normalized approximate f...
George A. Gravvanis, Konstantinos M. Giannoutakis