activity
20172021
most citedRobust PCA by Manifold Optimization

20 citations · 27 across the 5 of their papers we have counts for

collaborators

6 papers

math.OC2021

Orthogonal Trace-Sum Maximization: Tightness of the Semidefinite Relaxation and Guarantee of Locally Optimal Solutions

Joong-Ho Won, Teng Zhang, Hua Zhou

This paper studies an optimization problem on the sum of traces of matrix quadratic forms in semi-orthogonal matrices, which can be considered as a generalization of the synchr…

cs.LG2021

Exploring Adversarial Examples for Efficient Active Learning in Machine Learning Classifiers

Honggang Yu, Shihfeng Zeng, Teng Zhang +2

Machine learning researchers have long noticed the phenomenon that the model training process will be more effective and efficient when the training samples are densely sampled aro…

math.OC20193 cited

Tightness of the semidefinite relaxation for orthogonal trace-sum maximization

Teng Zhang

This paper studies an optimization problem on the sum of traces of matrix quadratic forms on orthogonal matrices, which can be considered as a generalization of the synchroniza…

math.ST20194 cited

Element-wise estimation error of a total variation regularized estimator for change point detection

Teng Zhang

This work studies the total variation regularized estimator (fused lasso) in the setting of a change point detection problem. Compared with existing works that focus on th…

math.ST2018

Phase Retrieval by Alternating Minimization with Random Initialization

Teng Zhang

We consider a phase retrieval problem, where the goal is to reconstruct a -dimensional complex vector from its phaseless scalar products with sensing vectors, independently…

stat.ML201720 cited

Robust PCA by Manifold Optimization

Teng Zhang, Yi Yang

Robust PCA is a widely used statistical procedure to recover a underlying low-rank matrix with grossly corrupted observations. This work considers the problem of robust PCA as a no…