首页|Northeast Normal University Reports Findings in Machine Learning (Shuffling-type gradient method with bandwidth-based step sizes for finite-sum optimization)
Northeast Normal University Reports Findings in Machine Learning (Shuffling-type gradient method with bandwidth-based step sizes for finite-sum optimization)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting from Changchun, People’s Repu blic of China, by NewsRx journalists, research stated, “Shufflingtypegradient method is a popular machine learning algorithm that solves finite-sum optimizati on problemsby randomly shuffling samples during iterations. In this paper, we e xplore the convergence properties ofshuffling-type gradient method under mild a ssumptions.”
ChangchunPeople’s Republic of ChinaA siaCyborgsEmerging TechnologiesMachine Learning
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