首页|Reports from Soochow University Highlight Recent Findings in Machine Learning (P owered Stochastic Optimization With Hypergradient Descent for Large-scale Learni ng Systems)
Reports from Soochow University Highlight Recent Findings in Machine Learning (P owered Stochastic Optimization With Hypergradient Descent for Large-scale Learni ng Systems)
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NETL
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Elsevier
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in Machine Learning. According to news reporting out of Suzhou, People’s Republic of China, by NewsRx editors, research stated, “Stochastic optimization (SO) algorithms based on the Powerball function, namely powered stochastic optimization (PoweredSO) algorith ms, have been confirmed, effectively, and demonstrated great potential in the co ntext of large-scale optimization and machine learning tasks. Nevertheless, the issue of how to determine the learning rate for PoweredSO is a challenge and sti ll unsolved problem.”
SuzhouPeople’s Republic of ChinaAsiaAlgorithmsCyborgsEmerging TechnologiesMachine LearningStochastic Optim izationSoochow University
NETL
NSTL
Elsevier
