4 citations · 6 across the 5 of their papers we have counts for
6 papers
Conditional Tensor Diffusion: Distributional Counterfactual Learning and Inference
Xinbing Kong, Zeyu Li, Junfan Mao +1
Causal inference guides operational and managerial decisions but remains challenging in high-dimensional panel or tensor settings, where decisions may depend on the joint condition…
Few-Round Distributed Principal Component Analysis: Closing the Statistical Efficiency Gap by Consensus
ZeYu Li, Xinsheng Zhang, Wang Zhou
Distributed algorithms and theories are called for in this era of big data. Under weaker local signal-to-noise ratios, we improve upon the celebrated one-round distributed principa…
Representational Transfer Learning for Matrix Completion
Yong He, Zeyu Li, Dong Liu +2
We propose to transfer representational knowledge from multiple sources to a target noisy matrix completion task by aggregating singular subspaces information. Under our representa…
Knowledge Transfer across Multiple Principal Component Analysis Studies
Zeyu Li, Kangxiang Qin, Yong He +2
Transfer learning has aroused great interest in the statistical community. In this article, we focus on knowledge transfer for unsupervised learning tasks in contrast to the superv…
Simultaneous Estimation and Dataset Selection for Transfer Learning in High Dimensions by a Non-convex Penalty
Zeyu Li, Dong Liu, Yong He +1
In this paper, we propose to estimate model parameters and identify informative source datasets simultaneously for high-dimensional transfer learning problems with the aid of a non…
Manifold Principle Component Analysis for Large-Dimensional Matrix Elliptical Factor Model
ZeYu Li, Yong He, Xinbing Kong +1
Matrix factor model has been growing popular in scientific fields such as econometrics, which serves as a two-way dimension reduction tool for matrix sequences. In this article, we…