Sharp global convergence guarantees for iterative nonconvex optimization with random data
Author:
Affiliation:
1. Department of Electrical Engineering, Stanford University
2. Schools of Industrial & Systems Engineering and Electrical & Computer Engineering, Georgia Tech
3. Department of Electrical & Computer Engineering, University of British Columbia
Publisher
Institute of Mathematical Statistics
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
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4. Bayati, M. and Montanari, A. (2012). The LASSO risk for Gaussian matrices. IEEE Trans. Inf. Theory 58 1997–2017.
5. Donoho, D. L., Maleki, A. and Montanari, A. (2011). The noise-sensitivity phase transition in compressed sensing. IEEE Trans. Inf. Theory 57 6920–6941.
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