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- Applied Mathematics
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.
- MATH 4900 : Supervised Research
- MATH 4901 : Supervised Reading
- MATH 7740 : Statistical Learning Theory: Classification, Pattern Recognition, Machine Learning
Interpolation under latent factor regression models: Generalization via low-dimensional adaptation (with Florentina Bunea and Seth Strimas-Mackey). arXiv:2002.02525.
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.
Inference in Interpretable Latent Factor Regression Models (with Xin Bing and Florentina Bunea). Bernoulli (2021) To appear.
Optimal estimation of sparse topic models (with Xin Bing and Florentina Bunea). Journal of Machine Learning Research 21, 1-45 (2020).
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).
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).
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).
Weak convergence of stationary empirical processes (with Dragan Radulovic). Journal of Statistical Planning and Inference, 149, 75-84 (2018).
Weak convergence of empirical copula processes indexed by functions (with Dragan Radulovic and Yue Zhao). Bernoulli, 23(4B), 3346-3384 (2017).