Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena. - Yunfei Lu; Linyun Yu; Peng Cui 001; Chengxi Zang; Renzhe Xu; Yihao Liu; Lei Li 005; Wenwu Zhu 001 (KDD, 2019)

Algorithmic Decision Making with Conditional Fairness. - Renzhe Xu; Peng Cui 001; Kun Kuang; Bo Li 064; Linjun Zhou; Zheyan Shen; Wei Cui (KDD, 2020)

Deep Stable Learning for Out-of-Distribution Generalization. - Xingxuan Zhang; Peng Cui 001; Renzhe Xu; Linjun Zhou; Yue He 001; Zheyan Shen (CVPR, 2021)

DARING: Differentiable Causal Discovery with Residual Independence. - Yue He 001; Peng Cui 001; Zheyan Shen; Renzhe Xu; Furui Liu; Yong Jiang 001 (KDD, 2021)

Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization. - Xingxuan Zhang; Linjun Zhou; Renzhe Xu; Peng Cui 001; Zheyan Shen; Haoxin Liu 002 (CoRR, 2021)

Towards Out-Of-Distribution Generalization: A Survey. - Zheyan Shen; Jiashuo Liu; Yue He 001; Xingxuan Zhang; Renzhe Xu; Han Yu 009; Peng Cui 001 (CoRR, 2021)

Why Stable Learning Works? A Theory of Covariate Shift Generalization. - Renzhe Xu; Peng Cui 001; Zheyan Shen; Xingxuan Zhang; Tong Zhang 001 (CoRR, 2021)

Towards Unsupervised Domain Generalization. - Xingxuan Zhang; Linjun Zhou; Renzhe Xu; Peng Cui 001; Zheyan Shen; Haoxin Liu 002 (CVPR, 2022)

NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges. - Xingxuan Zhang; Yue He 001; Tan Wang; Jiaxin Qi; Han Yu 009; Zimu Wang; Jie Peng; Renzhe Xu; Zheyan Shen; Yulei Niu; Hanwang Zhang; Peng Cui 001 (ECCV Workshops (6), 2022)

A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization. - Renzhe Xu; Xingxuan Zhang; Zheyan Shen; Tong Zhang 001; Peng Cui 001 (ICML, 2022)

Model Agnostic Sample Reweighting for Out-of-Distribution Learning. - Xiao Zhou; Yong Lin; Renjie Pi; Weizhong Zhang; Renzhe Xu; Peng Cui 001; Tong Zhang 001 (ICML, 2022)

Product Ranking for Revenue Maximization with Multiple Purchases. - Renzhe Xu; Xingxuan Zhang; Bo Li 064; Yafeng Zhang; Xiaolong Chen; Peng Cui 001 (NeurIPS, 2022)

Regulatory Instruments for Fair Personalized Pricing. - Renzhe Xu; Xingxuan Zhang; Peng Cui 001; Bo Li 064; Zheyan Shen; Jiazheng Xu (WWW, 2022)

Towards Domain Generalization in Object Detection. - Xingxuan Zhang; Zekai Xu; Renzhe Xu; Jiashuo Liu; Peng Cui 001; Weitao Wan; Chong Sun; Chen Li (CoRR, 2022)

Covariate-Shift Generalization via Random Sample Weighting. - Yue He 001; Xinwei Shen 002; Renzhe Xu; Tong Zhang 001; Yong Jiang 001; Wenchao Zou; Peng Cui 001 (AAAI, 2023)

Stable Learning via Sparse Variable Independence. - Han Yu 009; Peng Cui 001; Yue He 001; Zheyan Shen; Yong Lin; Renzhe Xu; Xingxuan Zhang (AAAI, 2023)

Factual Observation Based Heterogeneity Learning for Counterfactual Prediction. - Hao Zou 001; Haotian Wang 001; Renzhe Xu; Bo Li 064; Jian Pei 001; Ye Jun Jian; Peng Cui 001 (CLeaR, 2023)

NICO++: Towards Better Benchmarking for Domain Generalization. - Xingxuan Zhang; Yue He 001; Renzhe Xu; Han Yu 009; Zheyan Shen; Peng Cui 001 (CVPR, 2023)

Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization. - Xingxuan Zhang; Renzhe Xu; Han Yu 009; Hao Zou 001; Peng Cui 001 (CVPR, 2023)

Flatness-Aware Minimization for Domain Generalization. - Xingxuan Zhang; Renzhe Xu; Han Yu 009; Yancheng Dong; Pengfei Tian; Peng Cui 001 (ICCV, 2023)

Measure the Predictive Heterogeneity. - Jiashuo Liu; Jiayun Wu; Renjie Pi; Renzhe Xu; Xingxuan Zhang; Bo Li 064; Peng Cui 001 (ICLR, 2023)

Competing for Shareable Arms in Multi-Player Multi-Armed Bandits. - Renzhe Xu; Haotian Wang 001; Xingxuan Zhang; Bo Li 064; Peng Cui 001 (ICML, 2023)

Rethinking the Evaluation Protocol of Domain Generalization. - Han Yu 009; Xingxuan Zhang; Renzhe Xu; Jiashuo Liu; Yue He 001; Peng Cui 001 (CVPR, 2024)

Model-Agnostic Random Weighting for Out-of-Distribution Generalization. - Yue He 001; Pengfei Tian; Renzhe Xu; Xinwei Shen 002; Xingxuan Zhang; Peng Cui 001 (KDD, 2024)

On the Out-Of-Distribution Generalization of Multimodal Large Language Models. - Xingxuan Zhang; Jiansheng Li; Wenjing Chu; Junjia Hai; Renzhe Xu; Yuqing Yang; Shikai Guan; Jiazheng Xu; Peng Cui 001 (CoRR, 2024)

PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators. - Renzhe Xu; Haotian Wang 001; Xingxuan Zhang; Bo Li 064; Peng Cui 001 (CoRR, 2024)

The Limits of Interval-Regulated Price Discrimination. - Kamesh Munagala; Yiheng Shen 001; Renzhe Xu (CoRR, 2024)

Stable Cox regression for survival analysis under distribution shifts. - Shaohua Fan; Renzhe Xu; Qian Dong; Yue He 001; Cheng Chang; Peng Cui 001 (Nat. Mac. Intell., 2024)

COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts. - Jiansheng Li; Xingxuan Zhang; Hao Zou 001; Yige Guo; Renzhe Xu; Yilong Liu; Chuzhao Zhu; Yue He 001; Peng Cui 001 (CVPR, 2025)

On the Out-Of-Distribution Generalization of Large Multimodal Models. - Xingxuan Zhang; Jiansheng Li; Wenjing Chu; Junjia Hai; Renzhe Xu; Yuqing Yang; Shikai Guan; Jiazheng Xu; Liping Jing; Peng Cui 001 (CVPR, 2025)

Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study. - Xingxuan Zhang; Haoran Wang; Jiansheng Li; Yuan Xue; Shikai Guan; Renzhe Xu; Hao Zou 001; Han Yu 009; Peng Cui 001 (ICLR, 2025)

Error Slice Discovery via Manifold Compactness. - Han Yu 009; Jiashuo Liu; Hao Zou 001; Renzhe Xu; Yue He 001; Xingxuan Zhang; Peng Cui 001 (CoRR, 2025)

Sample Weight Averaging for Stable Prediction. - Han Yu 009; Yue He 001; Renzhe Xu; Dongbai Li; Jiayin Zhang; Wenchao Zou; Peng Cui 001 (CoRR, 2025)

Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources. - Renzhe Xu; Kang Wang; Bo Li 064 (CoRR, 2025)