首页|Researchers from Sichuan University Report Details of New Studies and Findings i n the Area of Machine Learning (An Accelerated Stochastic Admm for Nonconvex and Nonsmooth Finite-sum Optimization)
Researchers from Sichuan University Report Details of New Studies and Findings i n the Area of Machine Learning (An Accelerated Stochastic Admm for Nonconvex and Nonsmooth Finite-sum Optimization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting from Chengdu, People’s Republic of China , by NewsRx journalists, research stated, “The nonconvex and nonsmooth finite -s um optimization problem with linear constraint has attracted much attention in t he fields of artificial intelligence, computer, and mathematics, due to its wide applications in machine learning and the lack of efficient algorithms with conv incing convergence theories. A popular approach to solve it is the stochastic Al ternating Direction Method of Multipliers (ADMM), but most stochastic ADMM-type methods focus on convex models.” Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China (NSFC), Natural Science F oundation of Sichuan Province, China, Guangdong Basic and Applied Basic Research Foundation, China, Shaanxi Fundamental Science Research Project for Mathematics and Physics, China, Sichuan Youth Science and Technology Innovation Team, China .
ChengduPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningSichuan University
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