Rustem Islamov
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226
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ML×2Optimization and Control×2Stats ML×1Crypto×1
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2026
Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions
The paper proposes Byz-Clip21-SGD2M, a novel algorithm that achieves high-probability convergence guarantees for Federated Learning by integrating robust aggregation, double momentum, and clipping, relaxing restrictive assumptions found in prior work.
What's in a Smoothness Constant? Tighter Rates for Local SGD with Bounded Second-order Heterogeneity
This paper proves the conjecture that Local SGD outperforms Mini-batch SGD under bounded second-order heterogeneity for general convex objectives, improving the convergence guarantee and lower bounds.
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Papers
cs.LGmath.OCstat.MLTheoreticalRecentJul 16, 2026
What's in a Smoothness Constant? Tighter Rates for Local SGD with Bounded Second-order Heterogeneity
This paper proves the conjecture that Local SGD outperforms Mini-batch SGD under bounded second-order heterogeneity for general convex objectives, improving the convergence guarantee and lower bounds.
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cs.LGcs.CRmath.OCRecent