Alternating minimization is a popular approach to solve several optimization problems. In this work, we explore theoretical properties of this method (and its variants) for several non-convex optimization problems that feature prominently in several important areas such as recommendation systems, compressive sensing, computer vision etc.
P. Jain, S. Oh, Learning Mixtures of Discrete Product Distributions using Spectral Decompositions. Arxiv Preprint, 2013.
- A. Agarwal, A. Anandkumar, P. Jain, P. Netrapalli, R. Tandon, Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization. Arxiv Preprint, 2013.
- P. Jain, I. S. Dhillon, Provable Inductive Matrix Completion. Arxiv Preprint, 2013.
- P. Netrapalli, P. Jain, S. Sanghavi, Phase Retrieval using Alternating Minimization. NIPS 2013.
- P. Jain, P. Netrapalli, S. Sanghavi, Low-rank Matrix Completion using Alternating Minimization. STOC 2013.
Provable Alternating Minimization methods for Machine Learning related Problems. IISC Bangalore, January 2014.