TR2008-013

Sparse and Shift-Invariant Feature Extraction From Non-Negative Data
Citation: Smaragdis, P.; Raj, B.; Shashanka, M., "Sparse and Shift-Invariant Feature Extraction from Non-Negative Data", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), ISSN: 1520-6149, pp. 2069-2072, March 2008 (IEEE Xplore)
Date:August 2008
MERL Contact:Bhiksha Raj

In this paper we describe a technique that allows the extraction of multiple local shift-invariant features from analysis of non-negative data of arbitrary dimensionality. Our approach employs a probabilistic latent variable model with sparsity constraints. We demonstrate its utility by performing feature extraction in a variety of domains ranging from audio to images and video.

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