machine learning Articles

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    Our approach to building transparent and explainable AI systems

    October 7, 2021

    Co-authors: Parvez Ahammad, Kinjal Basu, Yazhou Cao, Shaunak Chatterjee, David Durfee, Sakshi Jain, Nihar Mehta, Varun Mithal, and Jilei Yang Delivering the best member and customer experiences with a focus on trust is core to everything that we do at LinkedIn. As we continue to build on our Responsible AI program that we recently outlined three months ago, a...

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    Using deep learning to detect abusive sequences of member activity

    September 2, 2021

    Co-authors: James Verbus and Beibei Wang The Anti-Abuse AI Team at LinkedIn creates, deploys, and maintains models that detect and prevent many types of abuse, including the creation of fake accounts, member profile scraping, automated spam, and account takeovers. As we prevent abuse using machine learning, there are several challenges we can face: Maximizing...

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    Lambda Learner: Nearline learning on data streams

    August 11, 2021

    Co-authors: Kirill Talanine, Jeffrey D. Gee, Rohan Ramanath, Konstantin Salomatin, Gungor Polatkan, Onkar Dalal, and Deepak Kumar Introduction A common challenge for production machine learning systems is reacting to change. The world can change quickly, particularly on a social network. This can range from sweeping changes at the scale of the whole economy...

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    DuaLip: Solving extreme-scale linear programs for web...

    August 6, 2021

    Co-authors: Kinjal Basu, Yao Pan, Rohan Ramanath, Konstantin Salomatin, Amol Ghoting, and S. Sathiya Keerthi Building thriving...

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    Optimizing People You May Know (PYMK) for equity in network...

    August 5, 2021

    Co-authors: Qiannan Yin, Yan Wang, Divya Venugopalan, Cyrus Diciccio, Heloise Logan, Preetam Nandy, Kinjal Basu, and Albert Cui...

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    TonY joins LF AI & Data Foundation

    July 15, 2021

    Co-authors: Keqiu Hu, Jonathan Hung, and Junfan Zhang Today, TonY is joining the LF AI & Data Foundation, an umbrella foundation of...