1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.OC2023★ 1 cited
Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing
Ziye Ma, Javad Lavaei, Somayeh Sojoudi
Gradient descent (GD) is crucial for generalization in machine learning models, as it induces implicit regularization, promoting compact representations. In this work, we examine t…
math.OC2023
Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
Ziye Ma, Igor Molybog, Javad Lavaei +1
This paper studies the role of over-parametrization in solving non-convex optimization problems. The focus is on the important class of low-rank matrix sensing, where we propose an…
math.OC2022
Semidefinite Programming versus Burer-Monteiro Factorization for Matrix Sensing
Baturalp Yalcin, Ziye Ma, Javad Lavaei +1
Many fundamental low-rank optimization problems, such as matrix completion, phase synchronization/retrieval, power system state estimation, and robust PCA, can be formulated as the…