首页|Reports from Hanoi University of Science and Technology Advance Knowledge in Mac hine Learning (Self-adaptive Algorithms for Quasiconvex Programming and Applicat ions To Machine Learning)
Reports from Hanoi University of Science and Technology Advance Knowledge in Mac hine Learning (Self-adaptive Algorithms for Quasiconvex Programming and Applicat ions To Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on Machine Learning have be en published. According to news reporting out of Hanoi, Vietnam, by NewsRx edito rs, research stated, "For solving a broad class of nonconvex programming problem s on an unbounded constraint set, we provide a self-adaptive step-size strategy that does not include line-search techniques and establishes the convergence of a generic approach under mild assumptions. Specifically, the objective function may not satisfy the convexity condition." Funders for this research include Tryyng Dstrok;yi hyc Bch Khoa H Nyi, Hanoi Uni versity of Science and Technology (HUST). Our news journalists obtained a quote from the research from the Hanoi Universit y of Science and Technology, "Unlike descent line-search algorithms, it does not need a known Lipschitz constant to figure out how big the first step should be. The crucial feature of this process is the steady reduction of the step size un til a certain condition is fulfilled. In particular, it can provide a new gradie nt projection approach to optimization problems with an unbounded constrained se t."
HanoiVietnamAsiaAlgorithmsCyborg sEmerging TechnologiesMachine LearningHanoi University of Science and Tech nology
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