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Zhaowei Zhu
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Cited by
Year
Learning with noisy labels revisited: A study using real-world human annotations
J Wei*, Z Zhu*, H Cheng, T Liu, G Niu, Y Liu
ICLR 2022, 2022
1952022
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
H Cheng*, Z Zhu*, X Li, Y Gong, X Sun, Y Liu
ICLR 2021, 2021
1942021
A Second-Order Approach to Learning with Instance-Dependent Label Noise
Z Zhu, T Liu, Y Liu
CVPR 2021 (oral), 2021
1272021
Federated bandit: A gossiping approach
Z Zhu, J Zhu, J Liu, Y Liu
Proceedings of the 2021 ACM SIGMETRICS/International Conference on …, 2021
822021
Clusterability as an alternative to anchor points when learning with noisy labels
Z Zhu, Y Song, Y Liu
ICML 2021 139, 12912-12923, 2021
812021
Detecting corrupted labels without training a model to predict
Z Zhu, Z Dong, Y Liu
International conference on machine learning, 27412-27427, 2022
572022
BLOT: Bandit learning-based offloading of tasks in fog-enabled networks
Z Zhu, T Liu, Y Yang, X Luo
IEEE Transactions on Parallel and Distributed Systems 30 (12), 2636-2649, 2019
512019
Beyond images: Label noise transition matrix estimation for tasks with lower-quality features
Z Zhu, J Wang, Y Liu
International Conference on Machine Learning, 27633-27653, 2022
392022
The rich get richer: Disparate impact of semi-supervised learning
Z Zhu, T Luo, Y Liu
ICLR 2022, 2022
312022
Mitigating Memorization of Noisy Labels via Regularization between Representations
H Cheng*, Z Zhu*, X Sun, Y Liu
ICLR 2023, 2023
30*2023
To aggregate or not? learning with separate noisy labels
J Wei, Z Zhu, T Luo, E Amid, A Kumar, Y Liu
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
202023
Time reusing in D2D-enabled cooperative networks
Z Zhu, S Jin, Y Yang, H Hu, X Luo
IEEE Transactions on Wireless Communications 17 (5), 3185-3200, 2018
202018
Learn and pick right nodes to offload
Z Zhu, T Liu, S Jin, X Luo
2018 IEEE Global Communications Conference (GLOBECOM), 1-6, 2018
152018
Optimal task offloading in fog-enabled networks via index policies
F Yang, Z Zhu, S Zhao, Y Yang, X Luo
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018
122018
CSI based high accuracy device free passive localization system
Y Liu, W Xiong, Z Zhu, S Li
2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 1-5, 2018
112018
Policy Learning Using Weak Supervision
J Wang*, H Guo*, Z Zhu*, Y Liu
Advances in Neural Information Processing Systems 34, 19960-19973, 2021
102021
Weak proxies are sufficient and preferable for fairness with missing sensitive attributes
Z Zhu, Y Yao, J Sun, H Li, Y Liu
International Conference on Machine Learning, 43258-43288, 2023
9*2023
Online optimal task offloading with one-bit feedback
S Zhao, Z Zhu, F Yang, X Luo
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018
82018
Alternate distributed allocation of time reuse patterns in Fog-enabled cooperative D2D networks
S Jin, Z Zhu, Y Yang, MT Zhou, X Luo
2017 IEEE Fog World Congress (FWC), 1-6, 2017
82017
Fairness improves learning from noisily labeled long-tailed data
J Wei, Z Zhu, G Niu, T Liu, S Liu, M Sugiyama, Y Liu
arXiv preprint arXiv:2303.12291, 2023
62023
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Articles 1–20