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We consider the problem of learning overcomplete dictionaries in the context of sparse coding, where each sample selects a sparse subset of dictionary elements.
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Ramsey theory reveals the conditions when sparse coding on subsampled data is unique
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Local stability and robustness of sparse dictionary learning in the presence of noise
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Exact recovery of sparsely-used dictionaries
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Learning sparsely used overcomplete dictionaries via alternating minimization
A. Agarwal, A. Anandkumar, P. Jain, P. Netrapalli, and R. Tandon · 2013
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