Decentralized SGD generalization error is bounded by O(init/(µNZ)) plus noise and heterogeneity terms, with a Byzantine-attack term that persists as sample size grows.
Generalization guarantee of decentralized learning with heterogeneous data,
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Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity
Decentralized SGD generalization error is bounded by O(init/(µNZ)) plus noise and heterogeneity terms, with a Byzantine-attack term that persists as sample size grows.