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JMLR
2010
202views more  JMLR 2010»
15 years 8 days ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
ICPR
2006
IEEE
16 years 6 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden
168
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FGR
2008
IEEE
254views Biometrics» more  FGR 2008»
15 years 6 months ago
Design sparse features for age estimation using hierarchical face model
A key point in automatic age estimation is to design feature set essential to age perception. To achieve this goal, this paper builds up a hierarchical graphical face model for fa...
Jin-Li Suo, Tianfu Wu, Song Chun Zhu, Shiguang Sha...
NECO
2007
127views more  NECO 2007»
15 years 5 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
ICIP
2000
IEEE
16 years 7 months ago
Image Compression with Geometrical Wavelets
We introduce a sparse image representation that takes advantage of the geometrical regularity of edges in images. A new class of one-dimensional wavelet orthonormal bases, called ...
Erwan Le Pennec, Stéphane Mallat