XIA, Dong

XIA, Dong is an Assistant Professor in the Department of Mathematics at The Hong Kong University of Science and Technology. His research interests include statistical machine learning, high dimensional statistics, optimization, and computational algorithms. He teaches MATH3424 Regression Analysis. Xia's work has been published in several top-tier journals, including the Journal of Machine Learning Research, the Journal of the American Statistical Association, and the Annals of Statistics. His publications cover topics such as quantile regression, matrix completion, and tensor decomposition.

Dong Xia is a researcher at the Hong Kong University of Science and Technology, specializing in Machine Learning, Statistics, Optimization, and Tensors. His work focuses on developing statistical and computational methods for tensor decomposition, low-rank tensor completion, and community detection in complex networks. Xia's research explores the theoretical limits and practical algorithms for estimating high-dimensional data structures, including tensor SVD, regularized tensor power iteration, and Riemannian optimization techniques. His publications address challenges in noisy matrix completion, singular subspace perturbation, and tensor-train format completion, contributing to both theoretical and applied aspects of tensor-based data analysis.