mlsanityData to 7 Oct 2026

Composite federated learning with heterogeneous data

arXiv 2309.01795 ↗First posted 4 Sep 2023cs.LG cs.DC math.OCcited by 7

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Abstract (arXiv)

We propose a novel algorithm for solving the composite Federated Learning (FL) problem. This algorithm manages non-smooth regularization by strategically decoupling the proximal operator and communication, and addresses client drift without any assumptions about data similarity. Moreover, each worker uses local updates to reduce the communication frequency with the server and transmits only a d-dimensional vector per communication round. We prove that our algorithm converges linearly to a neighborhood of the optimal solution and demonstrate the superiority of our algorithm over state-of-the-art methods in numerical experiments.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 16 of its 21 references that are in the map. First posted on arXiv 4 Sep 2023.

Builds on

16 of 21 references.

References · 16

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,592
  2. 2018Federated Optimization in Heterogeneous Networkscited by 2,971
  3. 2019On the Convergence of FedAvg on Non-IID Datacited by 1,220
  4. 2018Local SGD Converges Fast and Communicates Littlecited by 595
  5. 2020Mime: Mimicking Centralized Stochastic Algorithms in Federated Learningcited by 152
  6. 2020FedPD: A Federated Learning Framework with Optimal Rates and Adaptivity to Non-IID Datacited by 143
  7. 2020FedSplit: An algorithmic framework for fast federated optimizationcited by 108
  8. 2021Differentially Private Federated Learning on Heterogeneous Datacited by 74
  9. 2020Federated Composite Optimizationcited by 49
  10. 2022FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participationcited by 35
  11. 2021FedDR -- Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimizationcited by 29
  12. 2021Fusion of Federated Learning and Industrial Internet of Things: A Surveycited by 28
4 more
  1. 2023Local Exact-Diffusion for Decentralized Optimization and Learningcited by 24
  2. 2022FedAudio: A Federated Learning Benchmark for Audio Taskscited by 15
  3. 2022Fast Composite Optimization and Statistical Recovery in Federated Learningcited by 12
  4. 2018A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Ratescited by 11

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 2.

7 papers.

  1. 2024Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Datacited by 5
  2. 2025FedCanon: Non-Convex Composite Federated Learning with Efficient Proximal Operation on Heterogeneous Datacited by 4
  3. 2025Federated Learning on Riemannian Manifolds: A Gradient-Free Projection-Based Approachcited by 1
  4. 2025Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentumcited by 0
  5. 2025Beyond Scaffold: A Unified Spatio-Temporal Gradient Tracking Methodcited by 0
  6. 2026Achieving Linear Speedup for Composite Federated Learningcited by 0
  7. 2026Compressed Proximal Federated Learning for Non-Convex Composite Optimization on Heterogeneous Datacited by 0