12 citations · 21 across the 7 of their papers we have counts for
10 papers
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…
Principal Component Projection with Low-Degree Polynomials
Stephen D. Farnham, Lixin Shen, Bruce W. Suter
In this paper, we consider approximations of principal component projection (PCP) without explicitly computing principal components. This problem has been studied in several recent…
Analysis of Adaptive Short-time Fourier Transform-based Synchrosqueezing Transform
Haiyan Cai, Qingtang Jiang, Lin Li +1
Recently the study of modeling a non-stationary signal as a superposition of amplitude and frequency-modulated Fourier-like oscillatory modes has been a very active research area.…
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…
Extragradient Method in Optimization: Convergence and Complexity
Trong Phong Nguyen, Edouard Pauwels, Emile Richard +1
We consider the extragradient method to minimize the sum of two functions, the first one being smooth and the second being convex. Under the Kurdyka-Lojasiewicz assumption, we prov…
From error bounds to the complexity of first-order descent methods for convex functions
Jérôme Bolte, Trong Phong Nguyen, Juan Peypouquet +1
This paper shows that error bounds can be used as effective tools for deriving complexity results for first-order descent methods in convex minimization. In a first stage, this obj…
Finding Dantzig selectors with a proximity operator based fixed-point algorithm
Ashley Prater, Lixin Shen, Bruce W. Suter
In this paper, we study a simple iterative method for finding the Dantzig selector, which was designed for linear regression problems. The method consists of two main stages. The f…
Blind One-Bit Compressive Sampling
Lixin Shen, Bruce W. Suter
The problem of 1-bit compressive sampling is addressed in this paper. We introduce an optimization model for reconstruction of sparse signals from 1-bit measurements. The model tar…
General Linearized Polynomial Interpolation and Its Applications
Hongmei Xie, Zhiyuan Yan, Bruce W. Suter
In this paper, we first propose a general interpolation algorithm in a free module of a linearized polynomial ring, and then apply this algorithm to decode several important famili…
Rank Metric Decoder Architectures for Random Linear Network Coding with Error Control
Ning Chen, Zhiyuan Yan, Maximilien Gadouleau +2
While random linear network coding is a powerful tool for disseminating information in communication networks, it is highly susceptible to errors caused by various sources. Due to…