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20172022
most citedGradient Properties of Hard Thresholding Operator

3 citations · 4 across the 2 of their papers we have counts for

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8 papers · 1 filter

math.OC20223 cited

Gradient Properties of Hard Thresholding Operator

Saeed Damadi, Jinglai Shen

Sparse optimization receives increasing attention in many applications such as compressed sensing, variable selection in regression problems, and recently neural network compressio…

math.OC20211 cited

Nonconvex, Fully Distributed Optimization based CAV Platooning Control under Nonlinear Vehicle Dynamics

Jinglai Shen, Eswar Kumar H. Kammara, Lili Du

CAV platooning technology has received considerable attention in the past few years, driven by the next generation smart transportation systems. Unlike most of the existing platoon…

math.OC2021

A Penalty Decomposition Algorithm with Greedy Improvement for Mean-Reverting Portfolios with Sparsity and Volatility Constraints

Ahmad Mousavi, Jinglai Shen

Mean-reverting portfolios with few assets, but high variance, are of great interest for investors in financial markets. Such portfolios are straightforwardly profitable because the…

math.OC2021

Fully Distributed Optimization based CAV Platooning Control under Linear Vehicle Dynamics

Jinglai Shen, Eswar Kumar H. Kammara, Lili Du

This paper develops distributed optimization based, platoon centered CAV car following schemes, motivated by the recent interest in CAV platooning technologies. Various distributed…

math.OC2020

Column Partition based Distributed Algorithms for Coupled Convex Sparse Optimization: Dual and Exact Regularization Approaches

Jinglai Shen, Jianghai Hu, Eswar Kumar Hathibelagal Kammara

This paper develops column partition based distributed schemes for a class of large-scale convex sparse optimization problems, e.g., basis pursuit (BP), LASSO, basis pursuit denosi…

math.OC2019

Exact Support and Vector Recovery of Constrained Sparse Vectors via Constrained Matching Pursuit

Jinglai Shen, Seyedahmad Mousavi

Matching pursuit, especially its orthogonal version (OMP) and variations, is a greedy algorithm widely used in signal processing, compressed sensing, and sparse modeling. Inspired…