Fan Zhou

Selected Publications

Welcome to check my Google Scholar for a full list of my publications.

Journal Publications

On the Value of label and Semantic information in Domain Generalization
Fan Zhou, Yuyi Chen, Shichun Yang, Boyu Wang, and Brahim Chaib-draa
Neural Networks (NEUNET) Studied the Value of label and semantic information in DG problems.
Towards More General Loss and Setting in Unsupervised Domain Adaptation
Changjian Shui, Ruizhi Pu, Gezheng Xu, Jun Wen, Fan Zhou, Christian Gagné, Charles X. Ling, and Boyu Wang
IEEE Transactions on Knowledge and Data Engineering (TKDE), accepted Studied the Value of label and semantic information in DG problems.
Episodic Task Agnostic Contrastive Training for for Multi-task Learning
Fan Zhou*, Yuyi Chen*, Jun Wen, Qiuhao Zeng, Charles Ling, Shichun Yang, Boyu Wang (*=Equal Contribution)
Neural Networks (NEUNET) 2023 Task index agnostic MTL with Episodic Contrastive Learning methods.
Gap Minimization for Knowledge Sharing and Transfer
Boyu Wang , Jorge Mendez , Changjian Shui, Fan Zhou , Di Wu, Gezheng Xu, Christian Gagné, Eric Eaton
Journal of Machine Learning Research (JMLR) Performance Gap Minimization for Transfer learning.
On the Benefits of Two Dimensional Metric Learning
Di Wu*, Fan Zhou*, Boyu Wang, Chi Man Wong, Changjian Shui, Yuan Zhou, Qicheng Lao, Feng Wan (*=Equal Contribution)
IEEE Transactions on Knowledge and Data Engineering (TKDE) 2021
Theoretical analysis on two dimentional metric learning.

Discriminative Active Learning for Domain Adaptation
Fan Zhou, Changjian Shui, Shichun Yang, Bincheng Huang, Boyu Wang Brahim Chaib-draa
Knowledge-based Systems, 2021
Wasserstein adversarial active learning for domain adaptation.

Domain Generalization via Optimal Transport with Metric Similarity Learning
Fan Zhou, Zhuqing Jiang, Changjian Shui, Boyu Wang, Brahim Chaib-draa
Neurocomputing 2021 Constrain the class relations during the adversarial training process in domain generalization.

Task similarity estimation through adversarialmultitask neural network
Fan Zhou, Changjian Shui, Mahdieh Abbasi, Louis-Émile Robitaille, Boyu Wang, Christian Gagné
IEEE Transcations on Neural Networks and Learning Systems (TNNLS) 2021
Adversarial Multitask Neural Networks.

Conference Publications

Generalizing Across Temporal Domains with Koopman Operators
Qiuhao Zeng, Wei Wang, Fan Zhou , Gezheng Xu , Ruizhi Pu , Changjian Shui , Christian Gagné , Shichun Yang , Charles Ling, Boyu Wang
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2024 Domain Generalization in non-stationary environments.
Foresee What You Will Learn: Data Augmentation for Domain Generalizationin in Non-Stationary Environment
Qiuhao Zeng, Wei Wang, Fan Zhou , Charles Ling, Boyu Wang
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 Capturing transitions in evolving domain generalization via meta-learning
Multi-task Learning by Leveraging the Semantic Information
Fan Zhou Brahim Chaib-draa, Boyu Wang
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 Leveraging the label and semantic relations between tasks.
Deep Active Learning: Unified and Principled Method for Query and Training
Changjian Shui, Fan Zhou, Christian Gagné, Boyu Wang
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Wasserstein adversarial active learning

为学日益，为道日损