Efficient Matrix Sensing Using Rank-1 Gaussian Measurements

DOI10.1007/978-3-319-24486-0_1zbMath1471.68103OpenAlexW2286769582MaRDI QIDQ2835614

Inderjit S. Dhillon, Kai Zhong, Prateek Jain

Publication date: 30 November 2016

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-24486-0_1

zbMATH Keywords

matrix completioninductive learningalternating minimizationmatrix sensing

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Computational learning theory (68Q32) Matrix completion problems (15A83)

Related Items

Unnamed Item ⋮ Low-Rank Matrix Estimation from Rank-One Projections by Unlifted Convex Optimization

Cites Work

• Low rank matrix recovery from rank one measurements
• User-friendly tail bounds for sums of random matrices
• ROP: matrix recovery via rank-one projections
• Exact matrix completion via convex optimization
• Incoherence-Optimal Matrix Completion
• Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization
• Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
• Recovering Low-Rank Matrices From Few Coefficients in Any Basis
• Matrix Completion From a Few Entries
• The Power of Convex Relaxation: Near-Optimal Matrix Completion
• A Simpler Approach to Matrix Completion
• Low-rank matrix completion using alternating minimization

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