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ICML
2010
IEEE
13 years 8 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
ICASSP
2011
IEEE
12 years 11 months ago
Sparse coding and dictionary learning based on the MDL principle
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Ignacio Ramírez, Guillermo Sapiro
BMVC
2010
13 years 5 months ago
Insect Species Recognition using Sparse Representation
Insect species recognition is a typical application of image categorization and object recognition. Unlike generic image categorization datasets (such as the Caltech 101 dataset) ...
An Lu, Xin Hou, Chen Lin, Cheng-Lin Liu
NECO
2010
154views more  NECO 2010»
13 years 6 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
ICIP
2007
IEEE
14 years 9 months ago
Image Denoising with Nonparametric Hidden Markov Trees
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...