Interactive Byzantine-Resilient Gradient Coding for General Data Assignments
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911767686283264 |
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| author | Jain, Shreyas Maßny, Luis Hofmeister, Christoph Yaakobi, Eitan Bitar, Rawad |
| author_facet | Jain, Shreyas Maßny, Luis Hofmeister, Christoph Yaakobi, Eitan Bitar, Rawad |
| contents | We tackle the problem of Byzantine errors in distributed gradient descent within the Byzantine-resilient gradient coding framework. Our proposed solution can recover the exact full gradient in the presence of $s$ malicious workers with a data replication factor of only $s+1$. It generalizes previous solutions to any data assignment scheme that has a regular replication over all data samples. The scheme detects malicious workers through additional interactive communication and a small number of local computations at the main node, leveraging group-wise comparisons between workers with a provably optimal grouping strategy. The scheme requires at most $s$ interactive rounds that incur a total communication cost logarithmic in the number of data samples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_16915 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Interactive Byzantine-Resilient Gradient Coding for General Data Assignments Jain, Shreyas Maßny, Luis Hofmeister, Christoph Yaakobi, Eitan Bitar, Rawad Information Theory Distributed, Parallel, and Cluster Computing We tackle the problem of Byzantine errors in distributed gradient descent within the Byzantine-resilient gradient coding framework. Our proposed solution can recover the exact full gradient in the presence of $s$ malicious workers with a data replication factor of only $s+1$. It generalizes previous solutions to any data assignment scheme that has a regular replication over all data samples. The scheme detects malicious workers through additional interactive communication and a small number of local computations at the main node, leveraging group-wise comparisons between workers with a provably optimal grouping strategy. The scheme requires at most $s$ interactive rounds that incur a total communication cost logarithmic in the number of data samples. |
| title | Interactive Byzantine-Resilient Gradient Coding for General Data Assignments |
| topic | Information Theory Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2401.16915 |