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Zhen Fang
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Cited by
Year
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, 2020
1532020
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
1232021
Bridging the theoretical bound and deep algorithms for open set domain adaptation
L Zhong, Z Fang, F Liu, B Yuan, G Zhang, J Lu
IEEE transactions on neural networks and learning systems, 2021
962021
Learning from a complementary-label source domain: theory and algorithms
Y Zhang, F Liu, Z Fang, B Yuan, G Zhang, J Lu
IEEE Transactions on Neural Networks and Learning Systems 33 (12), 7667-7681, 2021
872021
Is Out-of-Distribution Detection Learnable?
Z Fang, Y Li, J Lu, J Dong, B Han, F Liu
NeurIPS 2022 Outstanding Paper Award, 2022
842022
Federated Class-Incremental Learning
J Dong, L Wang, Z Fang, G Sun, S Xu, X Wang, Q Zhu
CVPR2022, 2022
842022
Confident Anchor-Induced Multi-Source Free Domain Adaptation
J Dong, Z Fang, A Liu, G Sun, T Liu
NeurIPS 2021, https://proceedings.neurips.cc/paper/202, 2021
672021
Learning bounds for open-set learning
Z Fang, J Lu, A Liu, F Liu, G Zhang
International conference on machine learning, 3122-3132, 2021
512021
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
512020
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
412022
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
372020
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
132019
Moderately Distributional Exploration for Domain Generalization
R Dai, Y Zhang, Z Fang, B Han, X Tian
International Conference on Machine Learning (ICML 2023), 2023
82023
Learning to augment distributions for out-of-distribution detection
Q Wang, Z Fang, Y Zhang, F Liu, Y Li, B Han
NeurIPS 2023, 2023
52023
An extremely simple algorithm for source domain reconstruction
Z Fang, J Lu, G Zhang
IEEE Transactions on Cybernetics, 2023
32023
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection
Y Luo, Z Chen, Z Fang, Z Zhang, Z Huang, M Baktashmotlagh
ICCV, 2023
32023
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
32022
Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources
H Zheng, Q Wang, Z Fang, X Xia, F Liu, T Liu, B Han
NeurIPS 2023, 2023
22023
Invariant Learning via Probability of Sufficient and Necessary Causes
M Yang, Z Fang, Y Zhang, Y Du, F Liu, JF Ton, J Wang
NeurIPS 2023, 2023
22023
Detecting Out-of-distribution Data through In-distribution Class Prior
X Jiang, F Liu, Z Fang, H Chen, T Liu, F Zheng, B Han
International Conference on Machine Learning (ICML 2023), 2023
22023
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Articles 1–20