53 citations · 144 across the 20 of their papers we have counts for
20 papers
A Parallel Direct Eigensolver for Sequences of Hermitian Eigenvalue Problems with No Tridiagonalization
Shengguo Li, Xinzhe Wu, Jose E. Roman +3
In this paper, a Parallel Direct Eigensolver for Sequences of Hermitian Eigenvalue Problems with no tridiagonalization is proposed, denoted by \texttt{PDESHEP}, and it combines dir…
Bregman Proximal Gradient Algorithm with Extrapolation for a class of Nonconvex Nonsmooth Minimization Problems
Xiaoya Zhang, Roberto Barrio, M. Angeles Martinez +2
In this paper, we consider an accelerated method for solving nonconvex and nonsmooth minimization problems. We propose a Bregman Proximal Gradient algorithm with extrapolation(BPGe…
Training GANs with Centripetal Acceleration
Wei Peng, Yuhong Dai, Hui Zhang +1
Training generative adversarial networks (GANs) often suffers from cyclic behaviors of iterates. Based on a simple intuition that the direction of centripetal acceleration of an ob…
A linear time algorithm for multiscale quantile simulation
Chengcheng Huang, Housen Li, Lizhi Cheng +1
Change-point problems have appeared in a great many applications for example cancer genetics, econometrics and climate change. Modern multiscale type segmentation methods are consi…
Non-ergodic Complexity of Convex Proximal Inertial Gradient Descents
Tao Sun, Linbo Qiao, Dongsheng Li
The proximal inertial gradient descent is efficient for the composite minimization and applicable for broad of machine learning problems. In this paper, we revisit the computationa…
A convergence framework for inexact nonconvex and nonsmooth algorithms and its applications to several iterations
Tao Sun, Hao Jiang, Lizhi Cheng +1
In this paper, we consider the convergence of an abstract inexact nonconvex and nonsmooth algorithm. We promise a pseudo sufficient descent condition and a pseudo relative error co…
Iteratively Linearized Reweighted Alternating Direction Method of Multipliers for a Class of Nonconvex Problems
Tao Sun, Hao Jiang, Lizhi Cheng +1
In this paper, we consider solving a class of nonconvex and nonsmooth problems frequently appearing in signal processing and machine learning research. The traditional alternating…
Updating quadratic palindromic models with no spillover effect on unmeasured spectral data
Kang Zhao, Lizhi Cheng, Shengguo Li +1
This paper concerns the model updating problems with no spillover of the quadratic palindromic system
Accurate Quotient-Difference algorithm: error analysis, improvements and applications
Peibing Du, Roberto Barrio, Hao Jiang +1
The compensated quotient-difference (Compqd) algorithm is proposed along with some applications. The main motivation is based on the fact that the standard quotient-difference (qd)…
A note on alternating minimization algorithms: Bregman frame
Tao Sun, Lizhi Cheng
In this paper, we propose a Bregman frame for several classical alternating minimization algorithms. In the frame, these algorithms have uniform mathematical formulation. We also p…
A note on the convergence of nonconvex line search
Tao Sun, Lizhi Chenga, Hao Jiang
In this note, we consider the line search for a class of abstract nonconvex algorithm which have been deeply studied in the Kurdyka-Lojasiewicz theory. We provide a weak convergenc…
Variants of alternating minimization method with sublinear rates of convergence for convex optimization
Hui Zhang, Lizhi Cheng
The alternating minimization (AM) method is a fundamental method for minimizing convex functions whose variable consists of two blocks. How to efficiently solve each subproblems wh…
Projected shrinkage algorithm for box-constrained L1-minimization
Hui Zhang, Lizhi Cheng
Box-constrained L1-minimization can perform remarkably better than classical L1-minimization when correction box constraints are available. And also many practical L1-minimization…
Proximal linearized iteratively reweighted least squares for a class of nonconvex and nonsmooth problems
Hui Zhang, Tao Sun, Lizhi Cheng
For solving a wide class of nonconvex and nonsmooth problems, we propose a proximal linearized iteratively reweighted least squares (PL-IRLS) algorithm. We first approximate the or…
New bounds for circulant Johnson-Lindenstrauss embeddings
Hui Zhang, Lizhi Cheng
This paper analyzes circulant Johnson-Lindenstrauss (JL) embeddings which, as an important class of structured random JL embeddings, are formed by randomizing the column signs of a…
A dual algorithm for a class of augmented convex models
Hui Zhang, Lizhi Cheng, Wotao Yin
Convex optimization models find interesting applications, especially in signal/image processing and compressive sensing. We study some augmented convex models, which are perturbed…
Novel variational model for inpainting in the wavelet domain
Dai-Qiang Chen, Li-Zhi Cheng
Wavelet domain inpainting refers to the process of recovering the missing coefficients during the image compression or transmission stage. Recently, an efficient algorithm framewor…
Fast Linearized Alternating Direction Minimization Algorithm with Adaptive Parameter Selection for Multiplicative Noise Removal
Dai-Qiang Chen, Li-Zhi Cheng
Owing to the edge preserving ability and low computational cost of the total variation (TV), variational models with the TV regularization have been widely investigated in the fiel…
Necessary and sufficient conditions of solution uniqueness in minimization
Hui Zhang, Wotao Yin, Lizhi Cheng
This paper shows that the solutions to various convex minimization problems are \emph{unique} if and only if a common set of conditions are satisfied. This result applies…
Strongly Convex Programming for Exact Matrix Completion and Robust Principal Component Analysis
Hui Zhang, Jian-Feng Cai, Lizhi Cheng +1
The common task in matrix completion (MC) and robust principle component analysis (RPCA) is to recover a low-rank matrix from a given data matrix. These problems gained great atten…