979 citations · 1.5k across the 63 of their papers we have counts for
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Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equations
Haishan Ye, Dachao Lin, Zhihua Zhang
In this paper, we propose the greedy and random Broyden's method for solving nonlinear equations. Specifically, the greedy method greedily selects the direction to maximize a certa…
Approximate Newton Methods
Haishan Ye, Luo Luo, Zhihua Zhang
Many machine learning models involve solving optimization problems. Thus, it is important to deal with a large-scale optimization problem in big data applications. Recently, subsam…
Tighter bound of Sketched Generalized Matrix Approximation
Haishan Ye, Qiaoming Ye, Zhihua Zhang
Generalized matrix approximation plays a fundamental role in many machine learning problems, such as CUR decomposition, kernel approximation, and matrix low rank approximation. Esp…
A Simple Approach to Optimal CUR Decomposition
Haishan Ye, Yujun Li, Zhihua Zhang
Prior optimal CUR decomposition and near optimal column reconstruction methods have been established by combining BSS sampling and adaptive sampling. In this paper, we propose a ne…
A Scalable and Extensible Framework for Superposition-Structured Models
Shenjian Zhao, Cong Xie, Zhihua Zhang
In many learning tasks, structural models usually lead to better interpretability and higher generalization performance. In recent years, however, the simple structural models such…
Improved Analyses of the Randomized Power Method and Block Lanczos Method
Shusen Wang, Zhihua Zhang, Tong Zhang
The power method and block Lanczos method are popular numerical algorithms for computing the truncated singular value decomposition (SVD) and eigenvalue decomposition problems. Esp…
On the Global Convergence of Majorization Minimization Algorithms for Nonconvex Optimization Problems
Yangyang Kang, Zhihua Zhang, Wu-Jun Li
In this paper, we study the global convergence of majorization minimization (MM) algorithms for solving nonconvex regularized optimization problems. MM algorithms have received gre…
Fast Spectral Low Rank Matrix Approximation
Haishan Ye, Zhihua Zhang
First, we extend the results of approximate matrix multiplication from the Frobenius norm to the spectral norm. Second, We develop a class of fast approximate generalized linear re…
Group Orbit Optimization: A Unified Approach to Data Normalization
Shuchang Zhou, Zhihua Zhang, Xiaobing Feng
In this paper we propose and study an optimization problem over a matrix group orbit that we call \emph{Group Orbit Optimization} (GOO). We prove that GOO can be used to induce mat…