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个人简介
Research focus: Statistical learning meets (non)convex optimization to enable resource efficient AI/ML
Current topics: deep learning theory, resource efficiency, learning & control, transformers and attention
Our lab's focus is principled and empirically-impactful ML methods. High-level criteria for joining our team
Self-motivated and intellectually curious with how things (e.g. AI/ML systems) work
Strong background in applied math (stats, optimization) and machine learning methods
Research experience in ML theory OR innovative AI/ML algorithms
Current topics: deep learning theory, resource efficiency, learning & control, transformers and attention
Our lab's focus is principled and empirically-impactful ML methods. High-level criteria for joining our team
Self-motivated and intellectually curious with how things (e.g. AI/ML systems) work
Strong background in applied math (stats, optimization) and machine learning methods
Research experience in ML theory OR innovative AI/ML algorithms
研究兴趣
论文共 132 篇作者统计合作学者相似作者
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AAAI 2024no. 11 (2024): 11866-11873
International Conference on Artificial Intelligence and Statistics (2024): 685-693
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Jongho Park, Jaeseung Park, Zheyang Xiong, Nayoung Lee, Jaewoong Cho,Samet Oymak,Kangwook Lee,Dimitris Papailiopoulos
CoRR (2024)
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arxiv(2024)
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CoRR (2024)
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CoRR (2024)
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AAAI 2024no. 15 (2024): 16890-16898
IEEE CONTROL SYSTEMS LETTERS (2023): 3525-3530
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