activity
20232026
most citedOptimal subsampling for the Cox proportional hazards model with massive survival data

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ME2026

COINS: Any-Stage-Valid and Utility-Oriented Sequential Conformal Prediction

Wangcheng Li, Nan Qiao, Xu Guo +1

In clinical diagnosis, sequential screening, and cascaded prediction systems, information is often acquired in stages, with intermediate predictions guiding whether to act on the a…

stat.ME2025

Scalable and Distributed Individualized Treatment Rules for Massive Datasets

Nan Qiao, Wangcheng Li, Jingxiao Zhang +1

Synthesizing information from multiple data sources is crucial for constructing accurate individualized treatment rules (ITRs). However, privacy concerns often present significant…

stat.AP2025

Rank-based transfer learning for high-dimensional survival data with application to sepsis data

Nan Qiao, Haowei Jiang, Cunjie Lin

Sepsis remains a critical challenge due to its high mortality and complex prognosis. To address data limitations in studying MSSA sepsis, we extend existing transfer learning frame…

stat.ML2025

Efficient Distributed Learning over Decentralized Networks with Convoluted Support Vector Machine

Canyi Chen, Nan Qiao, Liping Zhu

This paper addresses the problem of efficiently classifying high-dimensional data over decentralized networks. Penalized support vector machines (SVMs) are widely used for high-dim…

stat.CO2023★ 1 cited

Optimal subsampling for the Cox proportional hazards model with massive survival data

Nan Qiao, Wangcheng Li, Feng Xiao +2

The use of massive survival data has become common in survival analysis. In this study, a subsampling algorithm is proposed for the Cox proportional hazards model with time-depende…