首页|New Machine Learning Findings from Swiss Federal Institute of Technology Describ ed (Stochastic Gradient Descent Without Full Data Shuffle: With Applications To In-database Machine Learning and Deep Learning Systems)
New Machine Learning Findings from Swiss Federal Institute of Technology Describ ed (Stochastic Gradient Descent Without Full Data Shuffle: With Applications To In-database Machine Learning and Deep Learning Systems)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting out of Zurich, Switzerland, b y NewsRx editors, research stated, “Modern machine learning (ML) systems commonl y use stochastic gradient descent (SGD) to train ML models. However, SGD relies on random data order to converge, which usually requires a full data shuffle.”
ZurichSwitzerlandEuropeCyborgsEm erging TechnologiesMachine LearningSwiss Federal Institute of Technology
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