Web: http://arxiv.org/abs/2201.06820

Jan. 26, 2022, 2:11 a.m. | Chong Chen, Fei Sun, Min Zhang, Bolin Ding

cs.LG updates on arXiv.org arxiv.org

Recommender systems provide essential web services by learning users'
personal preferences from collected data. However, in many cases, systems also
need to forget some training data. From the perspective of privacy, several
privacy regulations have recently been proposed, requiring systems to eliminate
any impact of the data whose owner requests to forget. From the perspective of
utility, if a system's utility is damaged by some bad data, the system needs to
forget these data to regain utility. From the perspective …


More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Product Manager (Europe, Remote)

@ FreshBooks | Germany

Field Operations and Data Engineer, ADAS

@ Lucid Motors | Newark, CA

Machine Learning Engineer - Senior

@ Novetta | Reston, VA

Analytics Engineer

@ ThirdLove | Remote

Senior Machine Learning Infrastructure Engineer - Safety

@ Discord | San Francisco, CA or Remote

Internship, Data Scientist

@ Everstream Analytics | United States (Remote)