20 citations · 23 across the 3 of their papers we have counts for
4 papers
Provable Bregman-divergence based Methods for Nonconvex and Non-Lipschitz Problems
Qiuwei Li, Zhihui Zhu, Gongguo Tang +1
The (global) Lipschitz smoothness condition is crucial in establishing the convergence theory for most optimization methods. Unfortunately, most machine learning and signal process…
Spherical Principal Component Analysis
Kai Liu, Qiuwei Li, Hua Wang +1
Principal Component Analysis (PCA) is one of the most important methods to handle high dimensional data. However, most of the studies on PCA aim to minimize the loss after projecti…
Global Optimality in Distributed Low-rank Matrix Factorization
Zhihui Zhu, Qiuwei Li, Xinshuo Yang +2
We study the convergence of a variant of distributed gradient descent (DGD) on a distributed low-rank matrix approximation problem wherein some optimization variables are used for…
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…