activity
20182022
most citedFinding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications

9 citations · 28 across the 4 of their papers we have counts for

collaborators

8 papers

cs.LG2021

A Geometric Analysis of Neural Collapse with Unconstrained Features

Zhihui Zhu, Tianyu Ding, Jinxin Zhou +4

We provide the first global optimization landscape analysis of -- an intriguing empirical phenomenon that arises in the last-layer classifiers and features of ne…

cs.LG20209 cited

Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications

Qing Qu, Zhihui Zhu, Xiao Li +3

The problem of finding the sparsest vector (direction) in a low dimensional subspace can be considered as a homogeneous variant of the sparse recovery problem, which finds applicat…

cs.LG20195 cited

Analysis of the Optimization Landscapes for Overcomplete Representation Learning

Qing Qu, Yuexiang Zhai, Xiao Li +2

We study nonconvex optimization landscapes for learning overcomplete representations, including learning (i) sparsely used overcomplete dictionaries and (ii) convolutional dictiona…

math.OC2019

Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods

Xiao Li, Shixiang Chen, Zengde Deng +3

We consider a class of nonsmooth optimization problems over the Stiefel manifold, in which the objective function is weakly convex in the ambient Euclidean space. Such problems are…

eess.SP2019

A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution

Qing Qu, Xiao Li, Zhihui Zhu

We study the multi-channel sparse blind deconvolution (MCS-BD) problem, whose task is to simultaneously recover a kernel and multiple sparse inputs $\{\mathbf x_i\}_{i=…

cs.LG2018

Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization

Zhihui Zhu, Xiao Li, Kai Liu +1

Symmetric nonnegative matrix factorization (NMF), a special but important class of the general NMF, is demonstrated to be useful for data analysis and in particular for various clu…