16 citations · 22 across the 5 of their papers we have counts for
5 papers · 1 filter
Optimal Estimation and Computational Limit of Low-rank Gaussian Mixtures
Zhongyuan Lyu, Dong Xia
Structural matrix-variate observations routinely arise in diverse fields such as multi-layer network analysis and brain image clustering. While data of this type have been extensiv…
Inference for Low-rank Tensors -- No Need to Debias
Dong Xia, Anru R. Zhang, Yuchen Zhou
In this paper, we consider the statistical inference for several low-rank tensor models. Specifically, in the Tucker low-rank tensor PCA or regression model, provided with any esti…
Statistical Inferences of Linear Forms for Noisy Matrix Completion
Dong Xia, Ming Yuan
We introduce a flexible framework for making inferences about general linear forms of a large matrix based on noisy observations of a subset of its entries. In particular, under mi…
Normal Approximation and Confidence Region of Singular Subspaces
Dong Xia
This paper is on the normal approximation of singular subspaces when the noise matrix has i.i.d. entries. Our contributions are three-fold. First, we derive an explicit representat…
Confidence Region of Singular Subspaces for Low-rank Matrix Regression
Dong Xia
Low-rank matrix regression refers to the instances of recovering a low-rank matrix based on specially designed measurements and the corresponding noisy outcomes. In the last decade…