Research Focus
Mathematical statistics, empirical process theory, high dimensional statistics and statistical learning theory.
My main research effort concentrates on developing new methodology in statistics and machine learning.
Publications
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Interpolation under latent factor regression models: Generalization via low-dimensional adaptation (with Florentina Bunea and Seth Strimas-Mackey). arXiv:2002.02525.
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Prediction in latent factor regression: Adaptive PCR and beyond (with Xin Bing, Florentina Bunea and Seth Strimas-Mackey). Journal of Machine Learning Research (2021) To appear.
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Inference in Interpretable Latent Factor Regression Models (with Xin Bing and Florentina Bunea). Bernoulli (2021) To appear.
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Optimal estimation of sparse topic models (with Xin Bing and Florentina Bunea). Journal of Machine Learning Research 21, 1-45 (2020).
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A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics (with Xin Bing and Florentina Bunea). Bernoulli 26(3), 1765-1796 (2020).
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Sparse Latent Factor Models with Pure Variables for Overlapping Clustering (Xin Bing, Florentina Bunea and Yang Ning). Annals of Statistics 48(4), 2055-2081 (2020).
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Adaptive estimation of the rank of the coefficient matrix in high dimensional multivariate response regression models (with Xin Bing). Annals of Statistics, 47(6), 3157-3184 (2019).
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Weak convergence of stationary empirical processes (with Dragan Radulovic). Journal of Statistical Planning and Inference, 149, 75-84 (2018).
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Weak convergence of empirical copula processes indexed by functions (with Dragan Radulovic and Yue Zhao). Bernoulli, 23(4B), 3346-3384 (2017).
MATH Courses - Fall 2023
- MATH 4900 : Supervised Research
- MATH 4901 : Supervised Reading
- MATH 7740 : Statistical Learning Theory