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• Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning
  2023 · 105 citations
• FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
  2022 · 53 citations
• Differentially Private Federated Learning on Heterogeneous Data
  2021 · 25 citations
• Bidirectional compression in heterogeneous settings for distributed or federated learning with partial participation: tight convergence guarantees
  2020 · 6 citations
• Compression with Exact Error Distribution for Federated Learning
  2023 · 4 citations
• QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning
  2021 · 3 citations
• A Tight Theory of Error Feedback Algorithms in Distributed Optimization
  2026
• From Inexact Gradients to Byzantine Robustness: Acceleration and Optimization under Similarity
  2026
• Tight Analysis of Decentralized SGD: A Markov Chain Perspective
  2026
• Federated Majorize-Minimization: Beyond Parameter Aggregation
  2025
• Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
  2025
• Refined Analysis of Federated Averaging and Federated Richardson-Romberg
  2024
• Byzantine-Robust Gossip: Insights from a Dual Approach
  2024