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Xiaofeng Liu 0009
Person information
- affiliation: Huawei Noah's Ark Lab, Beijing, China
- affiliation: Tianjin University, School of Electrical and Information Engineering, China
Other persons with the same name
- Xiaofeng Liu — disambiguation page
- Xiaofeng Liu 0001 — Harvard Medical School, Boston, MA, USA (and 2 more)
- Xiaofeng Liu 0002 — Beihang University, School of Transportation Science and Engineering, Beijing, China
- Xiaofeng Liu 0003 — Tianjin University of Technology and Education, School of Transportation and Automotive, China
- Xiaofeng Liu 0004 — Tianjin Medical University Cancer Institute and Hospital, Department of Molecular Radiation Oncology, China
- Xiaofeng Liu 0005 — East China University of Science and Technology, State Key Laboratory of Bioreactor Engineering, Shanghai, China (and 1 more)
- Xiaofeng Liu 0006 — Hohai University, Changzhou Key Laboratory of Robotics and Intelligent Technology, Changzhou, China
- Xiaofeng Liu 0007 — Zhejiang Normal University, College of Mathematics and Computer Science, Jinhua, China (and 2 more)
- Xiaofeng Liu 0008 — Chongqing University, State Key Laboratory of Mechanical Transmission for Advanced Equipment, China
- Xiaofeng Liu 0010 — Southeast University, National Mobile Communications Research Laboratory, China (and 1 more)
- Xiaofeng Liu 0011 — Peking University, Institute of Remote Sensing and Geographical Information System, School of Earth and Space Sciences, Beijing, China
- Xiaofeng Liu 0012 — Shanghai Jiaotong University, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, China
- Xiaofeng Liu 0013 — Shandong University, School of Cyber Science and Technology,
- Xiaofeng Liu 0014 — Digital Guangdong Network Construction Company, Guangzhou, China (and 1 more)
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2020 – today
- 2024
- [j5]Haozhi Wang, Qing Wang, Luyong Chen, Guanyang Fu, Xiaofeng Liu, Zhicheng Dong, Erdal Panayirci:
Breaking the Performance Gap of Fully and Semisupervised Learning in Electromagnetic Signature Recognition. IEEE Internet Things J. 11(2): 3161-3174 (2024) - [j4]Xiaofeng Liu, Qing Wang, Yunfeng Shao, Yinchuan Li:
Sparse Federated Learning With Hierarchical Personalization Models. IEEE Internet Things J. 11(5): 8539-8551 (2024) - [j3]Xiaofeng Liu, Yinchuan Li, Qing Wang, Xu Zhang, Yunfeng Shao, Yanhui Geng:
Sparse Personalized Federated Learning. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12027-12041 (2024) - 2023
- [c3]Jing Jin, Qing Wang, Xiaofeng Liu:
Heterogeneous Federated Learning with Cross-layer Model Fusion. ICCC 2023: 1-6 - 2022
- [i4]Xiaofeng Liu, Yinchuan Li, Yunfeng Shao, Qing Wang:
Sparse Federated Learning with Hierarchical Personalization Models. CoRR abs/2203.13517 (2022) - [i3]Qing Wang, Jing Jin, Xiaofeng Liu, Huixuan Zong, Yunfeng Shao, Yinchuan Li:
Tensor Decomposition based Personalized Federated Learning. CoRR abs/2208.12959 (2022) - 2021
- [j2]Chenyu Zhao, Qing Wang, Xiaofeng Liu, Chun Li, Lidong Shi:
Reinforcement learning based a non-zero-sum game for secure transmission against smart jamming. Digit. Signal Process. 112: 103002 (2021) - [c2]Huixuan Zong, Qing Wang, Xiaofeng Liu, Yinchuan Li, Yunfeng Shao:
Communication Reducing Quantization for Federated Learning with Local Differential Privacy Mechanism. ICCC 2021: 75-80 - [i2]Yinchuan Li, Xiaofeng Liu, Yunfeng Shao, Qing Wang, Yanhui Geng:
Structured Directional Pruning via Perturbation Orthogonal Projection. CoRR abs/2107.05328 (2021) - [i1]Yinchuan Li, Xiaofeng Liu, Xu Zhang, Yunfeng Shao, Qing Wang, Yanhui Geng:
Personalized Federated Learning via Maximizing Correlation with Sparse and Hierarchical Extensions. CoRR abs/2107.05330 (2021) - 2020
- [j1]Qing Wang, Panfei Du, Xiaofeng Liu, Jingyu Yang, Guohua Wang:
Adversarial unsupervised domain adaptation for cross scenario waveform recognition. Signal Process. 171: 107526 (2020) - [c1]Xiaofeng Liu, Qing Wang, Haozhi Wang:
A Two-Fold Group Lasso Based Lightweight Deep Neural Network for Automatic Modulation Classification. ICC Workshops 2020: 1-6
Coauthor Index
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last updated on 2024-12-11 21:44 CET by the dblp team
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