基本信息
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Bio
Michael C. (Mike) Hughes works on statistical machine learning. He develops methods that find useful structure in large, messy datasets and help people make decisions in the face of uncertainty. His research interests include Bayesian hierarchical models, optimization algorithms for approximate inference, model fairness and interpretability, and applications in medicine and the sciences. Active projects include helping clinicians understand and treat diseases like depression and infertility by training probabilistic models to make personalized drug recommendations for new patients based on the thousands of electronic health records observed from previous patients.
Research Interests
Papers共 79 篇Author StatisticsCo-AuthorSimilar Experts
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CoRR (2024)
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CoRR (2024)
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Shivam Goel,Panagiotis Lymperopoulos,Ravenna Thielstrom,Evan Krause,Patrick Feeney, Pierrick Lorang,Sarah Schneider, Yichen Wei, Eric Kildebeck, Stephen Goss,Michael C. Hughes,Liping Liu,
Artificial Intelligenceno. C (2024): 104111
CoRR (2023)
Benjamin S Wessler,Zhe Huang, Gary M Long,Stefano Pacifici, Nishant Prashar,Samuel Karmiy,Roman A Sandler,Joseph Z Sokol, Daniel B Sokol,Monica M Dehn,Luisa Maslon,Eileen Mai,
Proceedings of machine learning research (2023): 285-307
arXiv (Cornell University)pp.8373-8394, (2023)
arXiv (Cornell University) (2023)
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