Zheyan Shen

According to our database, Zheyan Shen authored at least 29 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Distributionally Robust Learning With Stable Adversarial Training.

Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li

IEEE Trans. Knowl. Data Eng., November, 2023

Meta Adaptive Task Sampling for Few-Domain Generalization.

Zheyan Shen, Han Yu, Peng Cui, Jiashuo Liu, Xingxuan Zhang, Linjun Zhou, Furui Liu

CoRR, 2023

NICO++: Towards Better Benchmarking for Domain Generalization.

Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Stable Learning via Sparse Variable Independence.

Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Distributionally Invariant Learning: Rationalization and Practical Algorithms.

Jiashuo Liu, Jiayun Wu, Jie Peng, Zheyan Shen, Bo Li, Peng Cui

CoRR, 2022

Regulatory Instruments for Fair Personalized Pricing.

Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization.

Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui

Proceedings of the International Conference on Machine Learning, 2022

Learning from Designers: Fashion Compatibility Analysis Via Dataset Distillation.

Yulan Chen, Zhiyong Wu, Zheyan Shen, Jia Jia

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges.

Xingxuan Zhang, Yue He, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, Peng Cui

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Towards Unsupervised Domain Generalization.

Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Towards Non-I.I.D. image classification: A dataset and baselines.

Yue He, Zheyan Shen, Peng Cui

Pattern Recognit., 2021

Why Stable Learning Works? A Theory of Covariate Shift Generalization.

Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, Tong Zhang

CoRR, 2021

Towards Out-Of-Distribution Generalization: A Survey.

Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui

CoRR, 2021

Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization.

Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu

CoRR, 2021

Kernelized Heterogeneous Risk Minimization.

Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DARING: Differentiable Causal Discovery with Residual Independence.

Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Heterogeneous Risk Minimization.

Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen

Proceedings of the 38th International Conference on Machine Learning, 2021

Deep Stable Learning for Out-of-Distribution Generalization.

Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Stable Adversarial Learning under Distributional Shifts.

Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Invariant Adversarial Learning for Distributional Robustness.

Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin

CoRR, 2020

Counterfactual Prediction for Bundle Treatment.

Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Algorithmic Decision Making with Conditional Fairness.

Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Stable Learning via Differentiated Variable Decorrelation.

Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Causal Inference Meets Machine Learning.

Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Stable Learning via Sample Reweighting.

Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

NICO: A Dataset Towards Non-I.I.D. Image Classification.

Yue He, Zheyan Shen, Peng Cui

CoRR, 2019

Measurement of blooming effect of DMSP-OLS nighttime light data based on NPP-VIIRS data.

Zheyan Shen, Xiaolin Zhu, Xin Cao, Jin Chen

Ann. GIS, 2019

2018

Causally Regularized Learning with Agnostic Data Selection Bias.

Zheyan Shen, Peng Cui, Kun Kuang, Bo Li, Peixuan Chen

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

2017

On Image Classification: Correlation v.s. Causality.

Zheyan Shen, Peng Cui, Kun Kuang, Bo Li

CoRR, 2017