5 papers
Functional linear regression from sparse to dense designs: a pooling-ridge method and minimax optimality
Shunxing Yan, Fang Yao
Functional data analysis is an important statistical field that treats data as random functions. In practice, the random functions are often not fully observed but instead measured…
Deconfounding via Profiled Transfer Learning
Ziyuan Chen, Yifan Jiang, Jingyuan Liu +1
Unmeasured confounders are a major source of bias in regression-based effect estimation and causal inference. In this paper, we propose a new profiled transfer learning framework,…
Deep Semiparametric Partial Differential Equation Models
Ziyuan Chen, Shunxing Yan, Fang Yao
In many scientific fields, the generation and evolution of data are governed by partial differential equations (PDEs) which are typically informed by established physical laws at t…
Semiparametric M-estimation with overparameterized neural networks
Shunxing Yan, Ziyuan Chen, Fang Yao
We focus on semiparametric regression that has played a central role in statistics, and exploit the powerful learning ability of deep neural networks (DNNs) while enabling statisti…
Matrix Completion via Residual Spectral Matching
Ziyuan Chen, Fang Yao
Noisy matrix completion has attracted significant attention due to its applications in recommendation systems, signal processing and image restoration. Most existing works rely on…