4 citations · 5 across the 3 of their papers we have counts for
4 papers
Modeling positive and unlabeled data with a generalized additive density ratio model
Peijun Sang, Yifan Sun, Qinglong Tian +2
This paper focuses on learning from positive and unlabeled (PU) data, where only some positives are labeled and the rest are mixed with negatives. Classical exponential tilting mod…
L1-Regularized Functional Support Vector Machine
Bingfan Liu, Peijun Sang
In functional data analysis, binary classification with one functional covariate has been extensively studied. We aim to fill in the gap of considering multivariate functional cova…
Kernel-based Method for Detecting Structural Break in Distribution of Functional Data
Peijun Sang, Bing Li
We propose a novel method to detect and date structural breaks in the entire distribution of functional data. Theoretical guarantees are developed for our procedure under fewer ass…
Nonlinear function-on-function regression by RKHS
Peijun Sang, Bing Li
We propose a nonlinear function-on-function regression model where both the covariate and the response are random functions. The nonlinear regression is carried out in two steps: w…