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Convex Block-sparse Linear Regression with Expanders - Provably., , , , , and . AISTATS, volume 51 of JMLR Workshop and Conference Proceedings, page 19-27. JMLR.org, (2016)Dropping Convexity for Faster Semi-definite Optimization., , and . CoRR, (2015)IHT dies hard: Provable accelerated Iterative Hard Thresholding., and . CoRR, (2017)SysML: The New Frontier of Machine Learning Systems., , , , , , , , , and 56 other author(s). CoRR, (2019)Provable quantum state tomography via non-convex methods., , , , , and . CoRR, (2017)Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably., , , and . SIAM J. Imaging Sciences, 11 (4): 2165-2204 (2018)Provable deterministic leverage score sampling., , and . KDD, page 997-1006. ACM, (2014)Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach., , , and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 65-74. PMLR, (2017)Stay on path: PCA along graph paths., , , , and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 1728-1736. JMLR.org, (2015)Group-Sparse Model Selection: Hardness and Relaxations, , , and . CoRR, (2013)