Adversary-Resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model

Author:

Yang ZhixiongORCID,Gang Arpita,Bajwa Waheed U.ORCID

Funder

Division of Computing and Communication Foundations

Defense Advanced Research Projects Agency

Army Research Office

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Signal Processing

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1. Byzantine fault tolerance in distributed machine learning: a survey;Journal of Experimental & Theoretical Artificial Intelligence;2024-09-12

2. Robust and privacy-preserving collaborative training: a comprehensive survey;Artificial Intelligence Review;2024-06-20

3. Resilient Formation-Tracking of Double-Integretor Multi-agent Systems against Byzantine Attacks;2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC);2024-06-07

4. Byzantine-robust decentralized stochastic optimization with stochastic gradient noise-independent learning error;Signal Processing;2024-06

5. D3: Dual-Domain Defenses for Byzantine-Resilient Decentralized Resource Allocation;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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