Zhen Fang-方震
Zhen Fang-方震
Postdoctoral Research Fellow, AAII,University of Technology Sydney
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Zitiert von
Zitiert von
Open set domain adaptation: Theoretical bound and algorithm
Z Fang, J Lu, F Liu, J Xuan, G Zhang
IEEE Transactions on Neural Networks and Learning Systems (Code: https …, 2020
Where and how to transfer: knowledge aggregation-induced transferability perception for unsupervised domain adaptation
J Dong, Y Cong, G Sun, Z Fang, Z Ding
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
How does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
L Zhong, Z Fang, F Liu, J Lu, B Yuan, G Zhang
Accepted By AAAI 2021, 2020
Learning bounds for open-set learning
Z Fang, J Lu, A Liu, F Liu, G Zhang
International conference on machine learning, 3122-3132, 2021
Clarinet: A one-step approach towards budget-friendly unsupervised domain adaptation
Y Zhang, F Liu, Z Fang, B Yuan, G Zhang, J Lu
accepted by IJCAI 2020., 2020
Confident Anchor-Induced Multi-Source Free Domain Adaptation
J Dong, Z Fang, A Liu, G Sun, T Liu
NeurIPS 2021,, 2021
Semi-supervised Heterogeneous Domain Adaptation: Theory and Algorithms
Z Fang, J Lu, F Liu, G Zhang
Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Unsupervised domain adaptation with sphere retracting transformation
Z Fang, J Lu, F Liu, G Zhang
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
Federated Class-Incremental Learning
J Dong, L Wang, Z Fang, G Sun, S Xu, X Wang, Q Zhu
CVPR2022, 2022
Is Out-of-Distribution Detection Learnable?
Z Fang, Y Li, J Lu, J Dong, B Han, F Liu
Neural Information Processing Systems 2022 Outstanding Paper Award, 2022
Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms
G Ma, J Lu, F Liu, Z Fang, G Zhang
Accepted by IEEE Transactions on Cybernetics, 2022
Bridging Theory and Algorithms for Open-Set and Heterogeneous Domain Adaptations
Z Fang
University of Technology Sydney, 2022
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