Unified Breakdown Analysis for Byzantine Robust Gossip
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866915335637041152 |
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| author | Gaucher, Renaud Dieuleveut, Aymeric Hendrikx, Hadrien |
| author_facet | Gaucher, Renaud Dieuleveut, Aymeric Hendrikx, Hadrien |
| contents | In decentralized machine learning, different devices communicate in a peer-to-peer manner to collaboratively learn from each other's data. Such approaches are vulnerable to misbehaving (or Byzantine) devices. We introduce F-RG, a general framework for building robust decentralized algorithms with guarantees arising from robust-sum-like aggregation rules F. We then investigate the notion of *breakdown point*, and show an upper bound on the number of adversaries that decentralized algorithms can tolerate. We introduce a practical robust aggregation rule, coined CS+, such that CS+-RG has a near-optimal breakdown. Other choices of aggregation rules lead to existing algorithms such as ClippedGossip or NNA. We give experimental evidence to validate the effectiveness of CS+-RG and highlight the gap with NNA, in particular against a novel attack tailored to decentralized communications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_10418 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Unified Breakdown Analysis for Byzantine Robust Gossip Gaucher, Renaud Dieuleveut, Aymeric Hendrikx, Hadrien Optimization and Control Machine Learning In decentralized machine learning, different devices communicate in a peer-to-peer manner to collaboratively learn from each other's data. Such approaches are vulnerable to misbehaving (or Byzantine) devices. We introduce F-RG, a general framework for building robust decentralized algorithms with guarantees arising from robust-sum-like aggregation rules F. We then investigate the notion of *breakdown point*, and show an upper bound on the number of adversaries that decentralized algorithms can tolerate. We introduce a practical robust aggregation rule, coined CS+, such that CS+-RG has a near-optimal breakdown. Other choices of aggregation rules lead to existing algorithms such as ClippedGossip or NNA. We give experimental evidence to validate the effectiveness of CS+-RG and highlight the gap with NNA, in particular against a novel attack tailored to decentralized communications. |
| title | Unified Breakdown Analysis for Byzantine Robust Gossip |
| topic | Optimization and Control Machine Learning |
| url | https://arxiv.org/abs/2410.10418 |