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2020 – today
- 2023
[j3]Jiashuo Liu
, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning With Stable Adversarial Training. IEEE Trans. Knowl. Data Eng. 35(11): 11288-11300 (2023)- [c18]Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang:
Stable Learning via Sparse Variable Independence. AAAI 2023: 10998-11006 - [c17]Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui:
NICO++: Towards Better Benchmarking for Domain Generalization. CVPR 2023: 16036-16047 - [i17]Zheyan Shen, Han Yu, Peng Cui, Jiashuo Liu, Xingxuan Zhang, Linjun Zhou, Furui Liu:
Meta Adaptive Task Sampling for Few-Domain Generalization. CoRR abs/2305.15644 (2023) - 2022
- [c16]Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu:
Towards Unsupervised Domain Generalization. CVPR 2022: 4900-4910 - [c15]Xingxuan Zhang, Yue He, Tan Wang, Jiaxin Qi, Han Yu, Zimu Wang, Jie Peng, Renzhe Xu, Zheyan Shen, Yulei Niu, Hanwang Zhang, Peng Cui:
NICO Challenge: Out-of-Distribution Generalization for Image Recognition Challenges. ECCV Workshops (6) 2022: 433-450 - [c14]Yulan Chen, Zhiyong Wu, Zheyan Shen, Jia Jia:
Learning from Designers: Fashion Compatibility Analysis Via Dataset Distillation. ICIP 2022: 856-860 - [c13]Renzhe Xu, Xingxuan Zhang, Zheyan Shen, Tong Zhang, Peng Cui:
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization. ICML 2022: 24803-24829 - [c12]Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu:
Regulatory Instruments for Fair Personalized Pricing. WWW 2022: 4-15 - [i16]Renzhe Xu, Xingxuan Zhang, Peng Cui, Bo Li, Zheyan Shen, Jiazheng Xu:
Regulatory Instruments for Fair Personalized Pricing. CoRR abs/2202.04245 (2022) - [i15]Xingxuan Zhang, Yue He, Renzhe Xu, Han Yu, Zheyan Shen, Peng Cui:
NICO++: Towards Better Benchmarking for Domain Generalization. CoRR abs/2204.08040 (2022) - [i14]Jiashuo Liu, Jiayun Wu, Jie Peng, Zheyan Shen, Bo Li, Peng Cui:
Distributionally Invariant Learning: Rationalization and Practical Algorithms. CoRR abs/2206.02990 (2022) - [i13]Han Yu, Peng Cui, Yue He, Zheyan Shen, Yong Lin, Renzhe Xu, Xingxuan Zhang:
Stable Learning via Sparse Variable Independence. CoRR abs/2212.00992 (2022) - 2021
- [j2]Yue He, Zheyan Shen, Peng Cui:
Towards Non-I.I.D. image classification: A dataset and baselines. Pattern Recognit. 110: 107383 (2021) - [c11]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Stable Adversarial Learning under Distributional Shifts. AAAI 2021: 8662-8670 - [c10]Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen:
Deep Stable Learning for Out-of-Distribution Generalization. CVPR 2021: 5372-5382 - [c9]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Heterogeneous Risk Minimization. ICML 2021: 6804-6814 - [c8]Yue He, Peng Cui, Zheyan Shen, Renzhe Xu, Furui Liu, Yong Jiang:
DARING: Differentiable Causal Discovery with Residual Independence. KDD 2021: 596-605 - [c7]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. NeurIPS 2021: 21720-21731 - [i12]Xingxuan Zhang, Peng Cui, Renzhe Xu, Linjun Zhou, Yue He, Zheyan Shen:
Deep Stable Learning for Out-Of-Distribution Generalization. CoRR abs/2104.07876 (2021) - [i11]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Heterogeneous Risk Minimization. CoRR abs/2105.03818 (2021) - [i10]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li:
Distributionally Robust Learning with Stable Adversarial Training. CoRR abs/2106.15791 (2021) - [i9]Xingxuan Zhang, Linjun Zhou, Renzhe Xu, Peng Cui, Zheyan Shen, Haoxin Liu:
Domain-Irrelevant Representation Learning for Unsupervised Domain Generalization. CoRR abs/2107.06219 (2021) - [i8]Zheyan Shen, Jiashuo Liu, Yue He, Xingxuan Zhang, Renzhe Xu, Han Yu, Peng Cui:
Towards Out-Of-Distribution Generalization: A Survey. CoRR abs/2108.13624 (2021) - [i7]Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen:
Kernelized Heterogeneous Risk Minimization. CoRR abs/2110.12425 (2021) - [i6]Renzhe Xu, Peng Cui, Zheyan Shen, Xingxuan Zhang, Tong Zhang:
Why Stable Learning Works? A Theory of Covariate Shift Generalization. CoRR abs/2111.02355 (2021) - 2020
- [c6]Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang:
Stable Learning via Sample Reweighting. AAAI 2020: 5692-5699 - [c5]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. KDD 2020: 2125-2135 - [c4]Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen:
Stable Learning via Differentiated Variable Decorrelation. KDD 2020: 2185-2193 - [c3]Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao:
Causal Inference Meets Machine Learning. KDD 2020: 3527-3528 - [c2]Hao Zou, Peng Cui, Bo Li, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He:
Counterfactual Prediction for Bundle Treatment. NeurIPS 2020 - [i5]Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang, Bo Li, Yishi Lin:
Invariant Adversarial Learning for Distributional Robustness. CoRR abs/2006.04414 (2020) - [i4]Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. CoRR abs/2006.10483 (2020)
2010 – 2019
- 2019
- [j1]Zheyan Shen, Xiaolin Zhu, Xin Cao, Jin Chen:
Measurement of blooming effect of DMSP-OLS nighttime light data based on NPP-VIIRS data. Ann. GIS 25(2): 153-165 (2019) - [i3]Yue He, Zheyan Shen, Peng Cui:
NICO: A Dataset Towards Non-I.I.D. Image Classification. CoRR abs/1906.02899 (2019) - [i2]Zheyan Shen, Peng Cui, Tong Zhang, Kun Kuang:
Stable Learning via Sample Reweighting. CoRR abs/1911.12580 (2019) - 2018
- [c1]Zheyan Shen, Peng Cui, Kun Kuang, Bo Li, Peixuan Chen:
Causally Regularized Learning with Agnostic Data Selection Bias. ACM Multimedia 2018: 411-419 - 2017
- [i1]Zheyan Shen, Peng Cui, Kun Kuang, Bo Li:
On Image Classification: Correlation v.s. Causality. CoRR abs/1708.06656 (2017)
Coauthor Index
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