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• From Local SGD to Local Fixed-Point Methods for Federated Learning
  2020 · 10 citations
• ProxSkip: Yes! Local Gradient Steps Provably Lead to Communication Acceleration! Finally!
  2022 · 10 citations
• Federated Learning with Regularized Client Participation
  2023 · 5 citations
• TAMUNA: Doubly Accelerated Distributed Optimization under Partial Participation
  2023 · 3 citations
• Federated Optimization Algorithms with Random Reshuffling and Gradient Compression
  2022 · 2 citations
• Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning
  2022 · 2 citations
• Improving Accelerated Federated Learning with Compression and Importance Sampling
  2023 · 2 citations
• Communication-Efficient Gluon in Federated Learning
  2026
• Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions
  2026
• First Provable Guarantees for Practical Private FL: Beyond Restrictive Assumptions
  2025
• Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
  2024
• Server-Side Stepsizes and Sampling Without Replacement Provably Help in Federated Optimization
  2022
• Federated Random Reshuffling with Compression and Variance Reduction
  2022
• Randomized Asymmetric Chain of LoRA: The First Meaningful Theoretical Framework for Low-Rank Adaptation
  2024