36 citations · 47 across the 12 of their papers we have counts for
6 papers · 1 filter
The Proximity Operator of the Log-Sum Penalty
Ashley Prater-Bennette, Lixin Shen, Erin E. Tripp
The log-sum penalty is often adopted as a replacement for the pseudo-norm in compressive sensing and low-rank optimization. The hard-thresholding operator, i.e., the proxi…
Regularization with Multilevel Non-stationary Tight Framelets for Image Restoration
Yan-ran Li, Raymond H. F. Chan, Lixin Shen +1
Variational regularization models are one of the popular and efficient approaches for image restoration. The regularization functional in the model carries prior knowledge about th…
Multiplicative Noise Removal: Nonlocal Low-Rank Model and Its Proximal Alternating Reweighted Minimization Algorithm
Xiaoxia Liu, Jian Lu, Lixin Shen +2
The goal of this paper is to develop a novel numerical method for efficient multiplicative noise removal. The nonlocal self-similarity of natural images implies that the matrices f…
On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit
Pranay Sharma, Prashant Khanduri, Lixin Shen +2
In this work, we consider a distributed online convex optimization problem, with time-varying (potentially adversarial) constraints. A set of nodes, jointly aim to minimize a globa…
Algorithmic Versatility of SPF-regularization Methods
Lixin Shen, Bruce W. Suter, Erin E. Tripp
Sparsity promoting functions (SPFs) are commonly used in optimization problems to find solutions which are assumed or desired to be sparse in some basis. For example, the l1-regula…
Structured Sparsity Promoting Functions
Lixin Shen, Bruce W. Suter, Erin E. Tripp
Motivated by the minimax concave penalty based variable selection in high-dimensional linear regression, we introduce a simple scheme to construct structured semiconvex sparsity pr…