3 citations · 3 across the 6 of their papers we have counts for
6 papers
Functional sufficient dimension reduction through information maximization with application to classification
Xinyu Li, Jianjun Xu, Wenquan Cui +1
Considering the case where the response variable is a categorical variable and the predictor is a random function, two novel functional sufficient dimensional reduction (FSDR) meth…
Federated Covariate Shift Adaptation for Missing Target Output Values
Yaqian Xu, Wenquan Cui, Jianjun Xu +1
The most recent multi-source covariate shift algorithm is an efficient hyperparameter optimization algorithm for missing target output. In this paper, we extend this algorithm to t…
Online Kernel Sliced Inverse Regression
Wenquan Cui, Yue Zhao, Jianjun Xu +1
Online dimension reduction is a common method for high-dimensional streaming data processing. Online principal component analysis, online sliced inverse regression, online kernel p…
Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression
Wenquan Cui, Yue Zhao, Jianjun Xu +1
Federated learning has become a popular tool in the big data era nowadays. It trains a centralized model based on data from different clients while keeping data decentralized. In t…
Copula approach to exchange-correlation hole in many-electron systems with strong correlations
JingChun Wang, Yu Su, Haoyang Cheng +2
Electronic correlation is a fundamental topic in many-electron systems. To characterize this correlation, one may introduce the concept of exchange-correlation hole. In this paper,…
Functional data clustering via information maximization
Xinyu Li, Jianjun Xu, Haoyang Cheng
A new method for clustering functional data is proposed via information maximization. The proposed method learns a probabilistic classifier in an unsupervised manner so that mutual…