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CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 9 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
CGF
2011
13 years 1 months ago
A Sparse Parametric Mixture Model for BTF Compression, Editing and Rendering
Bidirectional texture functions (BTFs) represent the appearance of complex materials. Three major shortcomings with BTFs are the bulky storage, the difficulty in editing and the ...
Hongzhi Wu, Julie Dorsey, Holly E. Rushmeier
SIAMIS
2008
211views more  SIAMIS 2008»
13 years 9 months ago
Sparse and Redundant Modeling of Image Content Using an Image-Signature-Dictionary
Modeling signals by sparse and redundant representations has been drawing considerable attention in recent years. Coupled with the ability to train the dictionary using signal exam...
Michal Aharon, Michael Elad
NECO
2008
114views more  NECO 2008»
13 years 9 months ago
A Sparse Generative Model of V1 Simple Cells with Intrinsic Plasticity
Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
Cornelius Weber, Jochen Triesch
CVPR
2005
IEEE
14 years 11 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman