@article{agarwal2016a,
author = {Agarwal, Alekh and Anandkumar, Animashree and Netrapalli, Praneeth},
title = {A Clustering Approach to Learn Sparsely-Used Overcomplete Dictionaries},
year = {2016},
month = {September},
abstract = {We consider the problem of learning overcomplete dictionaries in the context of sparse coding, where each sample selects a sparse subset of dictionary elements. Our main result is a strategy to approximately recover the unknown dictionary using an efficient algorithm. Our algorithm is a clustering-style procedure, where each cluster is used to estimate a dictionary element. The resulting solution can often be further cleaned up to obtain a high accuracy estimate, and we provide one simple scenario where ℓ1-regularized regression can be used for such a second stage.},
url = {http://approjects.co.za/?big=en-us/research/publication/exact-recovery-sparsely-used-overcomplete-dictionaries/},
journal = {IEEE Transcations on Information Theory},
}