3 papers
stat.ME2025
Model positive and unlabeled data with a generalized additive density ratio model
Peijun Sang, Yifan Sun, Qinglong Tian +2
We address learning from positive and unlabeled (PU) data, a common setting in which only some positives are labeled and the rest are mixed with negatives. Classical exponential ti…
stat.ML2025
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…
stat.ME2025
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…