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Aspis: A Robust Detection System for Distributed Learning. (arXiv:2108.02416v2 [cs.LG] UPDATED)
Jan. 6, 2022, 2:10 a.m. | Konstantinos Konstantinidis, Aditya Ramamoorthy
cs.LG updates on arXiv.org arxiv.org
State-of-the-art machine learning models are routinely trained on large-scale
distributed clusters. Crucially, such systems can be compromised when some of
the computing devices exhibit abnormal (Byzantine) behavior and return
arbitrary results to the parameter server (PS). This behavior may be attributed
to a plethora of reasons, including system failures and orchestrated attacks.
Existing work suggests robust aggregation and/or computational redundancy to
alleviate the effect of distorted gradients. However, most of these schemes are
ineffective when an adversary knows the task …
More from arxiv.org / cs.LG updates on arXiv.org
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