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Jun Li

Southwest University · CN
Area of research
Computer Networks and Communications · Artificial Intelligence
Research interest
Research topics from publications: A Distributed Nesterov-Like Gradient Tracking Algorithm for Composite Constrained Optimization. Representative work: This paper focuses on the constrained optimization problem where the objective function is composed of smooth (possibly nonconvex) and nonsmooth parts. The proposed algorithm integrates the successive convex approximation (SCA) technique with the gradient tracking mechanism that aims at achieving a linear convergence rate and employing the momentum term to regulate update directions in each time instant. It is proved that the proposed algorithm converges provided that the constant step size and momentum parameter are lower than the given upper bounds. When the smooth part is strongly convex, the proposed algorithm linearly converges to the global optimal solution, whereas it converges to a l
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Recent publications

A Distributed Nesterov-Like Gradient Tracking Algorithm for Composite Constrained Optimization
IEEE Transactions on Signal and Information Processing over Networks 2023cited by 13position: middledoi

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Frequent collaborators

Huaqing Li · Southwest University1 papers (2023–2023)Huiwei Wang · Chongqing University1 papers (2023–2023)Yawei Shi · Southwest University1 papers (2023–2023)Zheng Wang · Chongqing University1 papers (2023–2023)Dawen Xia · Southwest University1 papers (2023–2023)Lifeng Zheng · Southwest University1 papers (2023–2023)Qingguo Lü · Ministry of Education of the People's Republic of China1 papers (2023–2023)Lianghao Ji · Southwest University1 papers (2023–2023)Tao Dong · Southwest University1 papers (2023–2023)