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References (18)

[1]
Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligence
2025Edward Collins, Michel Wang
[2]
Encrypted Spiking Neural Networks Based on Adaptive Differential Privacy Mechanism
2025Xiwen Luo, Qiang Fu et al.
[3]
DA-LIF: Dual Adaptive Leaky Integrate-and-Fire Model for Deep Spiking Neural Networks
2025Tianqing Zhang, Kairong Yu et al.
[4]
The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning
2024Manh V. Nguyen, Liang Zhao et al.
[5]
SFedCA: Credit Assignment-Based Active Client Selection Strategy for Spiking Federated Learning
2024Qiugang Zhan, Jinbo Cao et al.
[6]
Towards Privacy-Preserving Federated Neuromorphic Learning via Spiking Neuron Models
2023Bing Han, Qiang Fu et al.
[7]
Efficient asynchronous federated neuromorphic learning of spiking neural networks
2023Yuan Wang, Shukai Duan et al.
[8]
Speech2Spikes: Efficient Audio Encoding Pipeline for Real-time Neuromorphic Systems
2023Kenneth Michael Stewart, Timothy M. Shea et al.
[9]
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
2023Yiğit Demirağ
[10]
Training Spiking Neural Networks Using Lessons From Deep Learning
2021J. Eshraghian, Max Ward et al.
[11]
Federated Learning With Spiking Neural Networks
2021Yeshwanth Venkatesha, Youngeun Kim et al.
[12]
Numerical Composition of Differential Privacy
2021Sivakanth Gopi, Y. Lee et al.
[13]
Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence
2019N. Skatchkovsky, Hyeryung Jang et al.
[14]
Bayesian Nonparametric Federated Learning of Neural Networks
2019M. Yurochkin, Mayank Agarwal et al.
[15]
How To Backdoor Federated Learning
2018Eugene Bagdasarian, Andreas Veit et al.
[16]
Deep Learning with Differential Privacy
2016Martín Abadi, Andy Chu et al.
[17]
Communication-Efficient Learning of Deep Networks from Decentralized Data
2016H. B. McMahan, Eider Moore et al.
[18]
Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition
2014W. Gerstner, W. M. Kistler et al.

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"Develops guidelines for privacy-preserving Federated Neuromorphic Learning using Differential Privacy mechanisms."

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