首页|Findings from East China Normal University Yields New Data on Machine Learning ( Fair Transfer Learning With Factor Variational Auto-encoder)
Findings from East China Normal University Yields New Data on Machine Learning ( Fair Transfer Learning With Factor Variational Auto-encoder)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating in Shanghai, People’s Re public of China, by NewsRx journalists, research stated, “Recently, in the field of fair machine learning, a large number of studies have considered how to remo ve discriminatory information from the data and achieve fairness in downstream t asks. Fair representation learning considers removing sensitive information (e.g . race, gender, etc) in the latent space, and the learned representations can pr event machine learning systems from being biased by discriminatory information.” Funders for this research include National Natural Science Foundation of China ( NSFC), Shanghai Municipal Project, Shanghai Knowledge Service Platform Project, Science & Technology Commission of Shanghai Municipality (STCSM), Open Research Fund of KLATASDS-MOE, Fundamental Research Funds for the Central U niversities.
ShanghaiPeople’s Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningEast China Normal Universi ty
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