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Hoda's current research is broadly concerned with the societal and economic aspects of Artificial Intelligence, and in particular, on issues of unfairness and inexplicability in Machine Learning. Hoda completed her doctoral studies in computer and information science at the University of Pennsylvania under the supervision of Professors Michael Kearns and Ali Jadbabaie. During her time at UPenn, she also obtained an M.Sc. degree in statistics from the Wharton school of business. Hoda has organized multiple events on the topic of her research, including a tutorial at the Web Conference (WWW) and a workshop at the Neural and Information Processing Systems (NeurIPS) conference.
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论文共 54 篇作者统计合作学者相似作者
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CoRR (2024)
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PROCEEDINGS OF THE 2023 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY, AIES 2023pp.38-48, (2023)
PROCEEDINGS OF 2023 ACM CONFERENCE ON EQUITY AND ACCESS IN ALGORITHMS, MECHANISMS, AND OPTIMIZATION, EAAMO 2023 (2023): 18:1-18:10
CoRR (2023)
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CoRRno. 5 (2023): 5974-5982
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PROCEEDINGS OF 2023 ACM CONFERENCE ON EQUITY AND ACCESS IN ALGORITHMS, MECHANISMS, AND OPTIMIZATION, EAAMO 2023 (2023): 36:1-36:11
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