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个人简介
His research interests revolve around the empirical and theoretical foundations of machine learning, often with a focus on reliable methods, datasets and evaluation paradigms. Schmidt’s research has led to more robust classification algorithms and new datasets and principles to probe the generalization capabilities of neural networks.
Schmidt is the recipient of a Google Ph.D. Fellowship, a Microsoft Simons Fellowship, a Best Paper Award from the International Conference on Machine Learning (ICML), and a Sprowls Dissertation Award from MIT.
Schmidt is the recipient of a Google Ph.D. Fellowship, a Microsoft Simons Fellowship, a Best Paper Award from the International Conference on Machine Learning (ICML), and a Sprowls Dissertation Award from MIT.
研究兴趣
论文共 109 篇作者统计合作学者相似作者
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CoRR (2024)
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Samir Yitzhak Gadre,Georgios Smyrnis,Vaishaal Shankar,Suchin Gururangan,Mitchell Wortsman,Rulin Shao,Jean Mercat,Alex Fang, Jeffrey Li, Sedrick Keh,Rui Xin,Marianna Nezhurina,
arxiv(2024)
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arxiv(2024)
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CoRR (2024)
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arxiv(2024)
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Anas Awadalla,Le Xue, Oscar Lo,Manli Shu, Hannah Lee, Etash Kumar Guha,Matt Jordan, Sheng Shen, Mohamed Awadalla,Silvio Savarese,Caiming Xiong,Ran Xu,
arxiv(2024)
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Jeffrey Li,Alex Fang,Georgios Smyrnis,Maor Ivgi,Matt Jordan,Samir Gadre,Hritik Bansal, Etash Guha, Sedrick Keh,Kushal Arora,Saurabh Garg,Rui Xin,
arxiv(2024)
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CHILpp.207-228, (2023)
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