72 citations · 542 across the 65 of their papers we have counts for
4 papers · 2 filters
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis +1
We consider the non-square matrix sensing problem, under restricted isometry property (RIP) assumptions. We focus on the non-convex formulation, where any rank- matrix $X \in \m…
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems
Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli +2
We study the projected gradient descent method on low-rank matrix problems with a strongly convex objective. We use the Burer-Monteiro factorization approach to implicitly enforce…
A simple and provable algorithm for sparse diagonal CCA
Megasthenis Asteris, Anastasios Kyrillidis, Oluwasanmi Koyejo +1
Given two sets of variables, derived from a common set of samples, sparse Canonical Correlation Analysis (CCA) seeks linear combinations of a small number of variables in each set,…
Trading-off variance and complexity in stochastic gradient descent
Vatsal Shah, Megasthenis Asteris, Anastasios Kyrillidis +1
Stochastic gradient descent is the method of choice for large-scale machine learning problems, by virtue of its light complexity per iteration. However, it lags behind its non-stoc…