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个人简介
My research interests revolve mainly around the theoretical properties of statistical and machine learning models for high-dimensional data under various structural assumptions, such as sparsity or intrinsic low dimensionality. In my research work I have investigated a broad range of issues related to the feasibility of statistical inference in a variety of problems, including high-dimensional regression, time series, privacy, categorical data analysis and graphical modeling, statistical network analysis, algebraic statistics, density-based clustering, topological and geometric data analysis and change-point detection. Though predominantly of theoretical nature, my research work is motivated by highly practical problems in data science and has direct methodological implications, as it aims at deriving theoretical guarantees in support of existing methods and algorithms.
研究兴趣
论文共 154 篇作者统计合作学者相似作者
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CoRR (2024)
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SIAM Journal on Mathematics of Data Scienceno. 1 (2024): 176-198
arXiv (Cornell University) (2023)
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arXiv (Cornell University) (2023)
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arXiv (Cornell University) (2023)
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CoRR (2023)
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arXiv (Cornell University) (2023)
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