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dSTAR: Straggler Tolerant and Byzantine Resilient Distributed SGD

DSTAR is proposed, a lightweight and efficient approach for distributed stochastic gradient descent that enhances robustness and convergence and outperforms other Byzantine-resilient methods that often suffer up to a 40-50\% accuracy drop under attack.

Jia Yan, Pratik Chaudhari, Leonard Kleinrock · 0 citations

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