Changjian Shui

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 48

Top Topics

Medical Imaging

Similarity Estimation

Domain Adaptation

Top Venues

Knowl. Based Syst.

IEEE Trans. Knowl. Data Eng.

Publications

Qiuhao Zeng, Changjian Shui, Long-Kai Huang, Peng Liu, Xi Chen, Charles Ling, Boyu Wang
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time. ICLR (2024)
Qiuhao Zeng, Wei Wang, Fan Zhou, Gezheng Xu, Ruizhi Pu, Changjian Shui, Christian Gagné, Shichun Yang, Boyu Wang, Charles X. Ling
Generalizing across Temporal Domains with Koopman Operators. CoRR (2024)
Qiuhao Zeng, Wei Wang, Fan Zhou, Gezheng Xu, Ruizhi Pu, Changjian Shui, Christian Gagné, Shichun Yang, Charles X. Ling, Boyu Wang
Generalizing across Temporal Domains with Koopman Operators. AAAI (2024)
Gezheng Xu, Qi Chen, Charles Ling, Boyu Wang, Changjian Shui
Intersectional Unfairness Discovery. CoRR (2024)
Qi Chen, Changjian Shui, Ligong Han, Mario Marchand
On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm. NeurIPS (2023)
Jiaqi Li, Haojia Kong, Gezheng Xu, Changjian Shui, Ruizhi Pu, Zhao Kang, Charles X. Ling, Boyu Wang
Label shift conditioned hybrid querying for deep active learning. Knowl. Based Syst. 274 (2023)
Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. MICCAI (3) (2023)
Raghav Mehta, Changjian Shui, Tal Arbel
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. MIDL (2023)
Changjian Shui, William Wei Wang, Ihsen Hedhli, Chi Man Wong, Feng Wan, Boyu Wang, Christian Gagné
Lifelong Online Learning from Accumulated Knowledge. ACM Trans. Knowl. Discov. Data 17 (4) (2023)
Changjian Shui, Ruizhi Pu, Gezheng Xu, Jun Wen, Fan Zhou, Christian Gagné, Charles X. Ling, Boyu Wang
Towards More General Loss and Setting in Unsupervised Domain Adaptation. IEEE Trans. Knowl. Data Eng. 35 (10) (2023)
Di Wu, Fan Zhou, Boyu Wang, Qicheng Lao, Chi Man Wong, Changjian Shui, Yuan Zhou, Feng Wan
On the Benefits of Two Dimensional Metric Learning. IEEE Trans. Knowl. Data Eng. 35 (2) (2023)
Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. CoRR (2023)
Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Gezheng Xu, Christian Gagné, Eric Eaton
Gap Minimization for Knowledge Sharing and Transfer. J. Mach. Learn. Res. 24 (2023)
Fan Zhou, Yuyi Chen, Jun Wen, Qiuhao Zeng, Changjian Shui, Charles X. Ling, Shichun Yang, Boyu Wang
Episodic task agnostic contrastive training for multi-task learning. Neural Networks 162 (2023)
Jiaqi Li, Rui Wang, Yuanhao Lai, Changjian Shui, Sabyasachi Sahoo, Charles X. Ling, Shichun Yang, Boyu Wang, Christian Gagné, Fan Zhou
Hessian Aware Low-Rank Weight Perturbation for Continual Learning. CoRR (2023)
Raghav Mehta, Changjian Shui, Tal Arbel
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis. CoRR (2023)
Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel
Information Gain Sampling for Active Learning in Medical Image Classification. CoRR (2022)
Boyu Wang, Jorge A. Mendez, Changjian Shui, Fan Zhou, Di Wu, Christian Gagné, Eric Eaton
Gap Minimization for Knowledge Sharing and Transfer. CoRR (2022)
Changjian Shui, Qi Chen, Jiaqi Li, Boyu Wang, Christian Gagné
Fair Representation Learning through Implicit Path Alignment. ICML (2022)
Changjian Shui, Boyu Wang, Christian Gagné
On the benefits of representation regularization in invariance based domain generalization. Mach. Learn. 111 (3) (2022)
Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles Ling, Tal Arbel, Boyu Wang, Christian Gagné
On Learning Fairness and Accuracy on Multiple Subgroups. CoRR (2022)
William Wei Wang, Gezheng Xu, Ruizhi Pu, Jiaqi Li, Fan Zhou, Changjian Shui, Charles X. Ling, Christian Gagné, Boyu Wang
Evolving Domain Generalization. CoRR (2022)
Changjian Shui, Qi Chen, Jun Wen, Fan Zhou, Christian Gagné, Boyu Wang
A novel domain adaptation theory with Jensen-Shannon divergence. Knowl. Based Syst. 257 (2022)
Changjian Shui, Gezheng Xu, Qi Chen, Jiaqi Li, Charles X. Ling, Tal Arbel, Boyu Wang, Christian Gagné
On Learning Fairness and Accuracy on Multiple Subgroups. NeurIPS (2022)
Anjun Hu, Jean-Pierre R. Falet, Brennan S. Nichyporuk, Changjian Shui, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors. CoRR (2022)
Changjian Shui, Qi Chen, Jiaqi Li, Boyu Wang, Christian Gagné
Fair Representation Learning through Implicit Path Alignment. CoRR (2022)
Raghav Mehta, Changjian Shui, Brennan Nichyporuk, Tal Arbel
Information Gain Sampling for Active Learning in Medical Image Classification. UNSURE@MICCAI (2022)
Qi Chen, Changjian Shui, Mario Marchand
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis. NeurIPS (2021)
Fan Zhou, Zhuqing Jiang, Changjian Shui, Boyu Wang, Brahim Chaib-draa
Domain generalization via optimal transport with metric similarity learning. Neurocomputing 456 (2021)
Fan Zhou, Changjian Shui, Shichun Yang, Bincheng Huang, Boyu Wang, Brahim Chaib-draa
Discriminative active learning for domain adaptation. Knowl. Based Syst. 222 (2021)
Qi Chen, Changjian Shui, Mario Marchand
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis. CoRR (2021)
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagné, Charles X. Ling, Boyu Wang
Aggregating From Multiple Target-Shifted Sources. CoRR (2021)
Changjian Shui, Boyu Wang, Christian Gagné
On the benefits of representation regularization in invariance based domain generalization. CoRR (2021)
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagné, Charles X. Ling, Boyu Wang
Aggregating From Multiple Target-Shifted Sources. ICML (2021)
Boyu Wang, Chi Man Wong, Zhao Kang, Feng Liu, Changjian Shui, Feng Wan, C. L. Philip Chen
Common Spatial Pattern Reformulated for Regularizations in Brain-Computer Interfaces. IEEE Trans. Cybern. 51 (10) (2021)
Fan Zhou, Changjian Shui, Mahdieh Abbasi, Louis-Émile Robitaille, Boyu Wang, Christian Gagné
Task Similarity Estimation Through Adversarial Multitask Neural Network. IEEE Trans. Neural Networks Learn. Syst. 32 (2) (2021)
Fan Zhou, Zhuqing Jiang, Changjian Shui, Boyu Wang, Brahim Chaib-draa
Domain Generalization with Optimal Transport and Metric Learning. CoRR (2020)
Changjian Shui, Fan Zhou, Christian Gagné, Boyu Wang
Deep Active Learning: Unified and Principled Method for Query and Training. AISTATS (2020)
Mahdieh Abbasi, Changjian Shui, Arezoo Rajabi, Christian Gagné, Rakesh B. Bobba
Toward Metrics for Differentiating Out-of-Distribution Sets. ECAI (2020)
Changjian Shui, Qi Chen, Jun Wen, Fan Zhou, Christian Gagné, Boyu Wang
Beyond H-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence. CoRR (2020)
Jun Wen, Changjian Shui, Kun Kuang, Junsong Yuan, Zenan Huang, Zhefeng Gong, Nenggan Zheng
Interventional Domain Adaptation. CoRR (2020)
Fan Zhou, Changjian Shui, Bincheng Huang, Boyu Wang, Brahim Chaib-draa
Discriminative Active Learning for Domain Adaptation. CoRR (2020)
Changjian Shui, Fan Zhou, Christian Gagné, Boyu Wang
Deep Active Learning: Unified and Principled Method for Query and Training. CoRR (2019)
Changjian Shui, Mahdieh Abbasi, Louis-Émile Robitaille, Boyu Wang, Christian Gagné
A Principled Approach for Learning Task Similarity in Multitask Learning. CoRR (2019)
Mahdieh Abbasi, Changjian Shui, Arezoo Rajabi, Christian Gagné, Rakesh Bobba
Toward Metrics for Differentiating Out-of-Distribution Sets. CoRR (2019)
Changjian Shui, Mahdieh Abbasi, Louis-Émile Robitaille, Boyu Wang, Christian Gagné
A Principled Approach for Learning Task Similarity in Multitask Learning. IJCAI (2019)
Changjian Shui, Ihsen Hedhli, Christian Gagné
Accumulating Knowledge for Lifelong Online Learning. CoRR (2018)
Changjian Shui, Azadeh Sadat Mozafari, Jonathan Marek, Ihsen Hedhli, Christian Gagné
Diversity regularization in deep ensembles. CoRR (2018)