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Learning efficient sparse and low rank models

IEEE Transactions on Pattern Analysis and Machine Intelligence, no. 99 (2015): 1

Cited by: 142|Views105
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Abstract

Parsimony, including sparsity and low rank, has been shown to successfully model data in numerous machine learning and signal processing tasks. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with parsimony-promoting terms. The inherently sequential structure and data-dependent c...More

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