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个人简介
My research interests include machine learning, information and coding theory, causality, and statistics. Currently, I am working on research problems that bridge fairness, explainability, policy, and law. Previously, I have also worked actively on problems in reliable computing for matrix multiplications and deep learning, laying the foun-dations for the emerging area of “coded computing.” I have a broad and diverse research experience, and a strong publication track record (with several follow-on works in reputed institutions and 500+ citations). My work has appeared in machine learning conferences, namely, NeurIPS, ICML, AAAI, AISTATS, BigData, as well as, theory-focused venues, namely, ISIT and IEEE Transactions on Information Theory.
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Entropyno. 5 (2023)
PROCEEDINGS OF THE 2023 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY, AIES 2023pp.443-453, (2023)
UAIpp.635-646, (2023)
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Trans. Mach. Learn. Res. (2023)
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