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ORCIDZhaowei Zhu
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Books and Theses
- 2023
[b1]Zhaowei Zhu:
Embracing Data-Centric AI: Practical and Provable Solutions to Weakly Supervised Data. University of California, Santa Cruz, USA, 2023
Journal Articles
- 2023
- [j5]Jian Ding
, Baoliu Liu, Jiaxin Wang, Ping Qiao, Zhaowei Zhu:
Digitalization of the Business Environment and Innovation Efficiency of Chinese ICT Firms. J. Organ. End User Comput. 35(3): 1-25 (2023) - 2021
- [j4]Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu:
Federated Bandit: A Gossiping Approach. Proc. ACM Meas. Anal. Comput. Syst. 5(1): 02:1-02:29 (2021) - 2019
- [j3]Zhaowei Zhu, Ting Liu, Yang Yang, Xiliang Luo:
BLOT: Bandit Learning-Based Offloading of Tasks in Fog-Enabled Networks. IEEE Trans. Parallel Distributed Syst. 30(12): 2636-2649 (2019) - 2018
- [j2]Shengda Jin, Zhaowei Zhu, Yuechen Wu, Sadiq Ali, Xiliang Luo:
Optimal Frequency Reuse in HetNets With In-Band Relays. IEEE Access 6: 67082-67094 (2018) - [j1]Zhaowei Zhu, Shengda Jin, Yang Yang, Honglin Hu, Xiliang Luo:
Time Reusing in D2D-Enabled Cooperative Networks. IEEE Trans. Wirel. Commun. 17(5): 3185-3200 (2018)
Conference and Workshop Papers
- 2024
- [c33]Xinyuan Ji, Zhaowei Zhu, Wei Xi, Olga Gadyatskaya, Zilong Song, Yong Cai, Yang Liu:
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning. AAAI 2024: 12830-12838 - [c32]Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu:
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models. ICLR 2024 - [c31]Jiawei Xu, Zhaowei Zhu, Weiwei Ye, Ning Gui:
Periodicity Association Based Contrastive Learning for Time Series Anomaly Detection. IJCNN 2024: 1-8 - 2023
- [c30]Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu:
To Aggregate or Not? Learning with Separate Noisy Labels. CSW@WSDM 2023: 8-43 - [c29]Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu:
Mitigating Memorization of Noisy Labels via Regularization between Representations. ICLR 2023 - [c28]Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Hang Li, Yang Liu:
Weak Proxies are Sufficient and Preferable for Fairness with Missing Sensitive Attributes. ICML 2023: 43258-43288 - [c27]Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu:
To Aggregate or Not? Learning with Separate Noisy Labels. KDD 2023: 2523-2535 - 2022
- [c26]Rui Tang, Zhaowei Zhu, Haishen Yao, Yanxuan Li, Xingzhi Sun, Gang Hu, Guotong Xie, Yichong Li:
Integrating Medical Code Descriptions and Building Text Classification Models for Diagnostic Decision Support. ICHI 2022: 612-613 - [c25]Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu:
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. ICLR 2022 - [c24]Zhaowei Zhu, Tianyi Luo, Yang Liu:
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning. ICLR 2022 - [c23]Zhaowei Zhu, Zihao Dong, Yang Liu:
Detecting Corrupted Labels Without Training a Model to Predict. ICML 2022: 27412-27427 - [c22]Zhaowei Zhu, Jialu Wang, Yang Liu:
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features. ICML 2022: 27633-27653 - 2021
- [c21]Zhaowei Zhu, Tongliang Liu, Yang Liu:
A Second-Order Approach to Learning With Instance-Dependent Label Noise. CVPR 2021: 10113-10123 - [c20]Rui Tang, Haishen Yao, Zhaowei Zhu, Xingzhi Sun, Gang Hu, Yichong Li, Guotong Xie:
Embedding Electronic Health Records to Learn BERT-based Models for Diagnostic Decision Support. ICHI 2021: 311-319 - [c19]Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu:
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. ICLR 2021 - [c18]Zhaowei Zhu, Yiwen Song, Yang Liu:
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels. ICML 2021: 12912-12923 - [c17]Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu:
Policy Learning Using Weak Supervision. NeurIPS 2021: 19960-19973 - [c16]Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu:
Federated Bandit: A Gossiping Approach. SIGMETRICS (Abstracts) 2021: 3-4 - 2020
- [c15]Zhaowei Zhu, Han Wang, Tingting Zhao, Yangming Guo, Zhuoyang Xu, Zhuo Liu, Siqi Liu, Xiang Lan, Xingzhi Sun, Mengling Feng:
Classification of Cardiac Abnormalities From ECG Signals Using SE-ResNet. CinC 2020: 1-4 - [c14]Jun Zong, Ting Liu, Zhaowei Zhu, Xiliang Luo, Hua Qian:
Social Bandit Learning: Strangers Can Help. WCSP 2020: 239-244 - 2019
- [c13]Ting Liu, Zhaowei Zhu, Junrong Gu, Xiliang Luo:
Learn to Offload in Mobile Edge Computing. GLOBECOM 2019: 1-6 - [c12]Guanxu Su, Jianghui Wen, Zhaowei Zhu, Zhuo Liu, Wei Zhao, Xingzhi Sun, Gang Hu, Guotong Xie:
An Approach of Integrating Domain Knowledge into Data-Driven Diagnostic Model. MedInfo 2019: 1594-1595 - 2018
- [c11]Shangshu Zhao, Zhaowei Zhu, Fuqian Yang, Xiliang Luo:
Online Optimal Task Offloading with One-Bit Feedback. GlobalSIP 2018: 683-687 - [c10]Fuqian Yang, Zhaowei Zhu, Shangshu Zhao, Yang Yang, Xiliang Luo:
Optimal Task Offloading in Fog-Enabled Networks via Index Policies. GlobalSIP 2018: 688-692 - [c9]Shengda Jin, Zhaowei Zhu, Cong Shen, Sadiq Ali, Hua Qian, Xiliang Luo:
Sparse Spectrum Reuse in HetNets with Relays. GLOBECOM 2018: 1-7 - [c8]Zhaowei Zhu, Ting Liu, Shengda Jin, Xiliang Luo:
Learn and Pick Right Nodes to Offload. GLOBECOM 2018: 1-6 - [c7]Yi Ding, Zhaowei Zhu, Yandong Wang, Zhongji Zhang, Kaiyuan Song, Li Ding:
Research on Τest of Anti-G Suits Αirbag Pressure. HCI (6) 2018: 352-366 - [c6]Hanyu Zhu, Fuqian Yang, Zhaowei Zhu, Xiliang Luo:
Optimal Interconnection for Massive MIMO Self-Calibration. ICC 2018: 1-6 - [c5]Yuge Liu, Wenhui Xiong, Zhaowei Zhu, Shaoqian Li:
CSI Based High Accuracy Device Free Passive Localization System. VTC Fall 2018: 1-5 - 2017
- [c4]Shengda Jin, Zhaowei Zhu, Yang Yang, Ming-Tuo Zhou, Xiliang Luo:
Alternate distributed allocation of time reuse patterns in Fog-enabled cooperative D2D networks. FWC 2017: 1-6 - [c3]Zhaowei Zhu, Shengda Jin, Yu Zeng, Honglin Hu, Xiliang Luo:
Optimal Time Reuse in Cooperative D2D Relaying Networks. GLOBECOM Workshops 2017: 1-6 - [c2]Shengda Jin, Zhaowei Zhu, Xuming Song, Sadiq Ali, Hua Qian, Xiliang Luo:
Estimation of sparse equivalent graph filters with limited observations. DSP 2017: 1-5 - [c1]Zhaowei Zhu, Shengda Jin, Xuming Song, Xiliang Luo:
Learning graph structure with stationary graph signals via first-order approximation. DSP 2017: 1-5
Informal and Other Publications
- 2024
- [i21]Jinlong Pang, Jialu Wang, Zhaowei Zhu, Yuanshun Yao, Chen Qian, Yang Liu:
Fair Classifiers Without Fair Training: An Influence-Guided Data Sampling Approach. CoRR abs/2402.12789 (2024) - [i20]Xinyuan Ji, Zhaowei Zhu, Wei Xi, Olga Gadyatskaya, Zilong Song, Yong Cai, Yang Liu:
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning. CoRR abs/2403.16561 (2024) - [i19]Zonglin Di, Zhaowei Zhu, Jinghan Jia, Jiancheng Liu, Zafar Takhirov, Bo Jiang, Yuanshun Yao, Sijia Liu, Yang Liu:
Label Smoothing Improves Machine Unlearning. CoRR abs/2406.07698 (2024) - 2023
- [i18]Jiaheng Wei, Zhaowei Zhu, Gang Niu, Tongliang Liu, Sijia Liu, Masashi Sugiyama, Yang Liu:
Fairness Improves Learning from Noisily Labeled Long-Tailed Data. CoRR abs/2303.12291 (2023) - [i17]Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu:
Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models. CoRR abs/2311.11202 (2023) - 2022
- [i16]Zhaowei Zhu, Jialu Wang, Yang Liu:
Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features. CoRR abs/2202.01273 (2022) - [i15]Jiaheng Wei, Zhaowei Zhu, Tianyi Luo, Ehsan Amid, Abhishek Kumar, Yang Liu:
To Aggregate or Not? Learning with Separate Noisy Labels. CoRR abs/2206.07181 (2022) - [i14]Zhaowei Zhu, Yuanshun Yao, Jiankai Sun, Yang Liu, Hang Li:
Evaluating Fairness Without Sensitive Attributes: A Framework Using Only Auxiliary Models. CoRR abs/2210.03175 (2022) - 2021
- [i13]Zhaowei Zhu, Xiang Lan, Tingting Zhao, Yangming Guo, Pipin Kojodjojo, Zhuoyang Xu, Zhuo Liu, Siqi Liu, Han Wang, Xingzhi Sun, Mengling Feng:
Identification of 27 abnormalities from multi-lead ECG signals: An ensembled Se-ResNet framework with Sign Loss function. CoRR abs/2101.03895 (2021) - [i12]Zhaowei Zhu, Yiwen Song, Yang Liu:
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels. CoRR abs/2102.05291 (2021) - [i11]Zhaowei Zhu, Tianyi Luo, Yang Liu:
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning. CoRR abs/2110.06282 (2021) - [i10]Zhaowei Zhu, Zihao Dong, Yang Liu:
A Good Representation Detects Noisy Labels. CoRR abs/2110.06283 (2021) - [i9]Hao Cheng, Zhaowei Zhu, Xing Sun, Yang Liu:
Demystifying How Self-Supervised Features Improve Training from Noisy Labels. CoRR abs/2110.09022 (2021) - [i8]Jiaheng Wei, Zhaowei Zhu, Hao Cheng, Tongliang Liu, Gang Niu, Yang Liu:
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations. CoRR abs/2110.12088 (2021) - 2020
- [i7]Jingkang Wang, Hongyi Guo, Zhaowei Zhu, Yang Liu:
Policy Learning Using Weak Supervision. CoRR abs/2010.01748 (2020) - [i6]Hao Cheng, Zhaowei Zhu, Xingyu Li, Yifei Gong, Xing Sun, Yang Liu:
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach. CoRR abs/2010.02347 (2020) - [i5]Zhaowei Zhu, Jingxuan Zhu, Ji Liu, Yang Liu:
Federated Bandit: A Gossiping Approach. CoRR abs/2010.12763 (2020) - [i4]Zhaowei Zhu, Tongliang Liu, Yang Liu:
A Second-Order Approach to Learning with Instance-Dependent Label Noise. CoRR abs/2012.11854 (2020) - 2018
- [i3]Zhaowei Zhu, Ting Liu, Shengda Jin, Xiliang Luo:
Learn and Pick Right Nodes to Offload. CoRR abs/1804.08416 (2018) - [i2]Shangshu Zhao, Zhaowei Zhu, Fuqian Yang, Xiliang Luo:
Online optimal task offloading with one-bit feedback. CoRR abs/1806.10547 (2018) - 2017
- [i1]Zhaowei Zhu, Shengda Jin, Yu Zeng, Honglin Hu, Xiliang Luo:
Optimal Time Reuse in Cooperative D2D Relaying Networks. CoRR abs/1706.03308 (2017)
Coauthor Index
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