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2020 – today
- 2023
[j8]Naifu Zhang
, Meixia Tao, Jia Wang, Shuo Shao:
Coded Over-the-Air Computation for Model Aggregation in Federated Learning. IEEE Commun. Lett. 27(1): 160-164 (2023)- [j7]Dong Wang, Naifu Zhang, Meixia Tao, Xu Chen:
Knowledge Selection and Local Updating Optimization for Federated Knowledge Distillation With Heterogeneous Models. IEEE J. Sel. Top. Signal Process. 17(1): 82-97 (2023) - [j6]Naifu Zhang, Meixia Tao, Jia Wang, Fan Xu:
Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach. IEEE Trans. Commun. 71(1): 173-186 (2023) - [j5]Zhiguang Feng, Rui-Bing Li, Naifu Zhang, Ligang Wu:
Event-Based Asymptotic Tracking Control for Constrained MIMO Nonlinear Systems via a Single-Parameter Adaptation Method. IEEE Trans. Syst. Man Cybern. Syst. 53(12): 7758-7768 (2023) - 2022
- [j4]Naifu Zhang, Meixia Tao:
A Low-Complexity and Adaptive Distributed Source Coding Design for Model Aggregation in Distributed Learning. IEEE Open J. Commun. Soc. 3: 2444-2460 (2022) - [c9]Jialing Chang, Naifu Zhang, Meixia Tao, Hu Tuo:
Federated Multi-Agent Reinforcement Learning for Collaborative Edge Caching in Content Delivery Networks. WCSP 2022: 166-170 - [i6]Naifu Zhang, Meixia Tao, Jia Wang, Fan Xu:
Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach. CoRR abs/2206.13984 (2022) - 2021
- [j3]Naifu Zhang, Xiaohe Yu, Xinchao Zhang, Sheena D'arcy:
HD-eXplosion: visualization of hydrogen-deuterium exchange data as chiclet and volcano plots with statistical filtering. Bioinform. 37(13): 1926-1927 (2021) - [j2]Naifu Zhang, Meixia Tao:
Gradient Statistics Aware Power Control for Over-the-Air Federated Learning. IEEE Trans. Wirel. Commun. 20(8): 5115-5128 (2021) - [c8]Naifu Zhang, Meixia Tao, Jia Wang:
Sum-Rate-Distortion Function for Indirect Multiterminal Source Coding in Federated Learning. ISIT 2021: 2161-2166 - [c7]Naifu Zhang, Nicholas Capel:
LEOC: A Principled Method in Integrating Reinforcement Learning and Classical Control Theory. L4DC 2021: 689-701 - [c6]Yuhong Deng, Di Guo, Xiaofeng Guo, Naifu Zhang, Huaping Liu, Fuchun Sun:
MQA: Answering the Question via Robotic Manipulation. Robotics: Science and Systems 2021 - [c5]Dong Wang, Naifu Zhang, Meixia Tao:
Adaptive Clustering-Based Model Aggregation for Federated Learning with Imbalanced Data. SPAWC 2021: 591-595 - [c4]Naifu Zhang, Meixia Tao:
An Adaptive Distributed Source Coding Design for Distributed Learning. WCSP 2021: 1-5 - [i5]Naifu Zhang, Meixia Tao, Jia Wang:
Rate Region for Indirect Multiterminal Source Coding in Federated Learning. CoRR abs/2101.08696 (2021) - 2020
- [c3]Naifu Zhang, Meixia Tao:
Gradient Statistics Aware Power Control for Over-the-Air Federated Learning in Fading Channels. ICC Workshops 2020: 1-6 - [i4]Naifu Zhang, Meixia Tao:
Gradient Statistics Aware Power Control for Over-the-Air Federated Learning in Fading Channels. CoRR abs/2003.02089 (2020) - [i3]Yuhong Deng, Naifu Zhang, Di Guo, Huaping Liu, Fuchun Sun, Chen Pang, Jing Pang:
MQA: Answering the Question via Robotic Manipulation. CoRR abs/2003.04641 (2020) - [i2]Nicholas Capel, Naifu Zhang:
Extended Radial Basis Function Controller for Reinforcement Learning. CoRR abs/2009.05866 (2020)
2010 – 2019
- 2018
- [j1]Naifu Zhang, Meixia Tao:
Fitness-Aware Coded Multicasting for Decentralized Caching With Finite File Packetization. IEEE Wirel. Commun. Lett. 7(5): 740-743 (2018) - [c2]Shengqi Hao, Naifu Zhang, Meixia Tao:
A Belief Propagation Approach for Caching Strategy Design in D2D Networks. ICC Workshops 2018: 1-6 - [c1]Naifu Zhang, Kaibin Zheng, Meixia Tao:
Using Grouped Linear Prediction and Accelerated Reinforcement Learning for Online Content Caching. ICC Workshops 2018: 1-6 - [i1]Naifu Zhang, Kaibin Zheng, Meixia Tao:
Using Grouped Linear Prediction and Accelerated Reinforcement Learning for Online Content Caching. CoRR abs/1803.04675 (2018)
Coauthor Index
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