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Parsa Moradi

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#machine learning Preprint Sep 2026

Manifold-Aware General Coded Computing for Straggler-Resilient Distributed Computing

Inspired by graph-based manifold learning, a manifold-aware encoding strategy for general coded computing (GCC) is proposed and experiments demonstrate that the proposed strategy consistently and significantly reduces the mean squared recovery error under straggling compared with standard GCC.

Parsa Moradi, M. Maddah-ali · 0 citations
#machine learning Preprint Aug 2026

Learning-Theoretic Foundation for General Coded Computing: The Straggler Setting

GCC formulates coded computing through a natural end-to-end mean-squared error loss that directly measures the discrepancy between the desired computations and their recovered estimates, and enables theoretical performance guarantees for GCC under two complementary straggler regimes.

Parsa Moradi, B. Tahmasebi, M. Maddah-ali · 0 citations

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