姜荣｜上海对外经贸大学｜学者主页

期刊论文

2026

基于联邦学习的统计诊断方法

龚笛，姜荣，张冠东

《微型电脑应用》

2026

A Family of Coherent Risk Measures: An Infinite Weighted Average of Value-at-Risk

Rong Jiang, M. C. Jones, Jiangfeng Wang, Keming Yu

Journal of Business and Economic Statistics

DOI

2026

Cheng et al's contribution to the Discussion of ‘Regression by composition’ by Farewell et al

Kaiming Cheng, Rong Jiang, Jiangfeng Wang, Keming Yu

Journal of the Royal Statistical Society Series B (Statistical Methodology)

DOI

2026

A communication-efficient distributed Retire with application to the analysis of multi-site air-quality distributed data

Rong Jiang, Jiangfeng Wang, Keming Yu

Journal of the Royal Statistical Society Series C (Applied Statistics)

DOI

2026

Jiangfeng Wang, Rong Jiang, Keming Yu’s contribution to the Discussion of ‘Augmented balancing weights as linear regression’ by Bruns-Smith et al.

Jiangfeng Wang, Keming Yu, Rong Jiang

Journal of the Royal Statistical Society Series B (Statistical Methodology)

DOI

2025

分布式数据集的稳健统计诊断

胡冠浩，姜荣

《上海第二工业大学学报》

DOI

2025

Distributed Composite Quantile Regression for High-Dimensional Data

Jiayuan Liang, Yi-Yang Zhou, Rong Jiang

Sankhya A

DOI

2024

流数据下的复合分位数回归

韩星敏，姜荣

《上海第二工业大学学报》

2024

分布式系统下基于分位数回归的统计诊断

陈实，姜荣

《上海第二工业大学学报》

2016

线性测量误差模型的随机加权分位数回归

刘莹，葛悠美，姜荣

《东华大学学报(自然科学版)》

预印本

2025

Average quantile regression: a new non-mean regression model and coherent risk measure

Keming Yu, Rong Jiang, M. C. Jones, Jiangfeng Wang

SSRN Electronic Journal

DOI

2025

Semi-supervised learning for linear extremile regression

Rong Jiang, Keming Yu, Jiangfeng Wang

arXiv preprint

2023

Modile as a conservative tail risk measurer: the solution of an optimisation problem with 0-1 loss function

Keming Yu, Rong Jiang, Chi Tim Ng

arXiv preprint

2023

Root n consistent extremile regression and its supervised and semi-supervised learning

Rong Jiang, Keming Yu

arXiv preprint

姜荣

精选作品

期刊论文

基于联邦学习的统计诊断方法

A Family of Coherent Risk Measures: An Infinite Weighted Average of Value-at-Risk

Cheng et al's contribution to the Discussion of ‘Regression by composition’ by Farewell et al

A communication-efficient distributed Retire with application to the analysis of multi-site air-quality distributed data

Jiangfeng Wang, Rong Jiang, Keming Yu’s contribution to the Discussion of ‘Augmented balancing weights as linear regression’ by Bruns-Smith et al.

分布式数据集的稳健统计诊断

Distributed Composite Quantile Regression for High-Dimensional Data

流数据下的复合分位数回归

分布式系统下基于分位数回归的统计诊断

线性测量误差模型的随机加权分位数回归

预印本

Average quantile regression: a new non-mean regression model and coherent risk measure

Semi-supervised learning for linear extremile regression

Modile as a conservative tail risk measurer: the solution of an optimisation problem with 0-1 loss function

Root n consistent extremile regression and its supervised and semi-supervised learning

研究方向