8 citations · 33 across the 33 of their papers we have counts for
34 papers
Tracking Tensor Ring Decompositions of Streaming Tensors
Yajie Yu, Hanyu Li
Tensor ring (TR) decomposition is an efficient approach to discover the hidden low-rank patterns for higher-order tensors, and streaming tensors are becoming highly prevalent in re…
Block-Randomized Stochastic Methods for Tensor Ring Decomposition
Yajie Yu, Hanyu Li, Jingchun Zhou
Tensor ring (TR) decomposition is a simple but effective tensor network for analyzing and interpreting latent patterns of tensors. In this work, we propose a doubly randomized opti…
Least product relative error estimation for functional multiplicative model and optimal subsampling
Qian Yan, Hanyu Li
In this paper, we study the functional linear multiplicative model based on the least product relative error criterion. Under some regularization conditions, we establish the consi…
Subsampling for tensor least squares: Optimization and statistical perspectives
Ling Tang, Hanyu Li
In this paper, we investigate the random subsampling method for tensor least squares problem with respect to the popular t-product. From the optimization perspective, we present th…
Randomized block subsampling Kaczmarz-Motzkin method
Yanjun Zhang, Hanyu Li
By introducing a subsampling strategy, we propose a randomized block Kaczmarz-Motzkin method for solving linear systems. Such strategy not only determines the block size, but also…
Practical Alternating Least Squares for Tensor Ring Decomposition
Yajie Yu, Hanyu Li
Tensor ring (TR) decomposition has been widely applied as an effective approach in a variety of applications to discover the hidden low-rank patterns in multidimensional data. A we…
On sketch-and-project methods for solving tensor equations
Ling Tang, Yanjun Zhang, Hanyu Li
We first propose the regular sketch-and-project method for solving tensor equations with respect to the popular t-product. Then, three adaptive sampling strategies and three corres…
Greedy capped nonlinear Kaczmarz methods
Yanjun Zhang, Hanyu Li
To solve nonlinear problems, we construct two kinds of greedy capped nonlinear Kaczmarz methods by setting a capped threshold and introducing an effective probability criterion for…
Greedy randomized sampling nonlinear Kaczmarz methods
Yanjun Zhang, Hanyu Li, Ling Tang
The nonlinear Kaczmarz method was recently proposed to solve the system of nonlinear equations. In this paper, we first discuss two greedy selection rules, i.e., the maximum residu…
Practical Sketching-Based Randomized Tensor Ring Decomposition
Yajie Yu, Hanyu Li
Based on sketching techniques, we propose two randomized algorithms for tensor ring (TR) decomposition. Specifically, by defining new tensor products and investigating their proper…
Optimal Subsampling for High-dimensional Ridge Regression
Hanyu Li, Chengmei Niu
We investigate the feature compression of high-dimensional ridge regression using the optimal subsampling technique. Specifically, based on the basic framework of random sampling a…
On Convergence Lemma and Convergence Stability for Piecewise Analytic Functions
Xiaotie Deng, Hanyu Li, Ningyuan Li
In this work, a convergence lemma for function being finite compositions of analytic mappings and the maximum operator is proved. The lemma shows that the set of -stationary…
Splitting-based randomized iterative methods for solving indefinite least squares problem
Yanjun Zhang, Hanyu Li
The indefinite least squares (ILS) problem is a generalization of the famous linear least squares problem. It minimizes an indefinite quadratic form with respect to a signature mat…
Sketch-and-project methods for tensor linear systems
Ling Tang, Yajie Yu, Yanjun Zhang +1
For tensor linear systems with respect to the popular t-product, we first present the sketch-and-project method and its adaptive variants. Their Fourier domain versions are also in…
Componentwise perturbation analysis for the generalized Schur decomposition
Guihua Zhang, Hanyu Li, Yimin Wei
By defining two important terms called basic perturbation vectors and obtaining their linear bounds, we obtain the linear componentwise perturbation bounds for unitary factors and…
On Tightness of Tsaknakis-Spirakis Descent Methods for Approximate Nash Equilibria
Zhaohua Chen, Xiaotie Deng, Wenhan Huang +2
This article explores the minimum approximation ratio for Nash equilibrium in bi-matrix games, focusing on the Tsaknakis and Spirakis (TS) methods. The previous SOTA, TS algorithm,…
Convergence directions of the randomized Gauss--Seidel method and its extension
Yanjun Zhang, Hanyu Li
The randomized Gauss--Seidel method and its extension have attracted much attention recently and their convergence rates have been considered extensively. However, the convergence…
Optimal Sampling Algorithms for Block Matrix Multiplication
Chengmei Niu, Hanyu Li
In this paper, we investigate the randomized algorithms for block matrix multiplication from random sampling perspective. Based on the A-optimal design criterion, the optimal sampl…
Preconvergence of the randomized extended Kaczmarz method
Yanjun Zhang, Hanyu Li
In this paper, we analyze the convergence behavior of the randomized extended Kaczmarz (REK) method for all types of linear systems (consistent or inconsistent, overdetermined or u…
A Block-Randomized Stochastic Method with Importance Sampling for CP Tensor Decomposition
Yajie Yu, Hanyu Li
One popular way to compute the CANDECOMP/PARAFAC (CP) decomposition of a tensor is to transform the problem into a sequence of overdetermined least squares subproblems with Khatri-…
Block sampling Kaczmarz-Motzkin methods for consistent linear systems
Yanjun Zhang, Hanyu Li
The sampling Kaczmarz-Motzkin (SKM) method is a generalization of the randomized Kaczmarz and Motzkin methods. It first samples some rows of coefficient matrix randomly to build a…
Greedy Motzkin-Kaczmarz methods for solving linear systems
Yanjun Zhang, Hanyu Li
The famous greedy randomized Kaczmarz (GRK) method uses the greedy selection rule on maximum distance to determine a subset of the indices of working rows. In this paper, with the…
A novel greedy Gauss-Seidel method for solving large linear least squares problem
Yanjun Zhang, Hanyu Li
We present a novel greedy Gauss-Seidel method for solving large linear least squares problem. This method improves the greedy randomized coordinate descent (GRCD) method proposed r…
A Count Sketch Kaczmarz Method For Solving Large Overdetermined Linear Systems
Yanjun Zhang, Hanyu Li
In this paper, combining count sketch and maximal weighted residual Kaczmarz method, we propose a fast randomized algorithm for large overdetermined linear systems. Convergence ana…