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Research
I'm interested in the foundations of machine learning with a focus on robustness, security, and reliability. My research emphasizes principled approaches to improving robustness and generalization, particularly under distribution shift or adversarial manipulation. Much of my work develops new models of data—both theoretical and conceptual—to help understand and solve failure modes of existing methods. I also frequently study questions in representation learning: when representations are identifiable and efficiently learnable, how they arise during training, and how to ensure they will robustly generalize.
I'm interested in the foundations of machine learning with a focus on robustness, security, and reliability. My research emphasizes principled approaches to improving robustness and generalization, particularly under distribution shift or adversarial manipulation. Much of my work develops new models of data—both theoretical and conceptual—to help understand and solve failure modes of existing methods. I also frequently study questions in representation learning: when representations are identifiable and efficiently learnable, how they arise during training, and how to ensure they will robustly generalize.
研究兴趣
论文共 17 篇作者统计合作学者相似作者
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CoRR (2023)
arXiv (Cornell University) (2023)
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