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» Coding Time-Varying Signals Using Sparse, Shift-Invariant Re...
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ICASSP
2010
IEEE
13 years 5 months ago
Hierarchical dictionary learning for invariant classification
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
Leah Bar, Guillermo Sapiro
ICASSP
2011
IEEE
12 years 9 months ago
Approximate nearest-subspace representations for sound mixtures
In this paper we present a novel approach to describe sound mixtures which is based on a geometric viewpoint. In this approach we extend the idea of a nearest-neighbor representat...
Paris Smaragdis
ICASSP
2011
IEEE
12 years 9 months ago
Collaborative sources identification in mixed signals via hierarchical sparse modeling
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on CHiLasso, a convex collaborative hierarchical s...
Pablo Sprechmann, Ignacio Ramírez, Pablo Ca...
NIPS
2004
13 years 6 months ago
Learning Efficient Auditory Codes Using Spikes Predicts Cochlear Filters
The representation of acoustic signals at the cochlear nerve must serve a wide range of auditory tasks that require exquisite sensitivity in both time and frequency. Lewicki (2002...
Evan C. Smith, Michael S. Lewicki
CVPR
2010
IEEE
13 years 9 months ago
Local Features Are Not Lonely - Laplacian Sparse Coding for Image Classification
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
Shenghua Gao, Wai-Hung Tsang, Liang-Tien Chia, Pei...