mlsanityData to 14 Oct 2026

Communication-Constrained Private Decentralized Online Personalized Mean Estimation

arXiv 2511.04702 ↗First posted 2 Nov 2025cs.SI cs.IT cs.LGcited by 0

Not on the map. Why?

Abstract (arXiv)

We consider the problem of communication-constrained collaborative personalized mean estimation under a privacy constraint in an environment of several agents continuously receiving data according to arbitrary unknown agent-specific distributions. A consensus-based algorithm is studied under the framework of differential privacy in order to protect each agent's data. We give a theoretical convergence analysis of the proposed consensus-based algorithm for any bounded unknown distributions on the agents' data, showing that collaboration provides faster convergence than a fully local approach where agents do not share data, under an oracle decision rule and under some restrictions on the privacy level and the agents' connectivity, which illustrates the benefit of private collaboration in an online setting under a communication restriction on the agents. The theoretical faster-than-local convergence guarantee is backed up by several numerical results.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 20 references that are in the map. First posted on arXiv 2 Nov 2025.

Builds on

13 of 20 references.

References · 13

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
  2. 2019Federated Learning: Challenges, Methods, and Future Directionscited by 1,538
  3. 2016Federated Learning: Strategies for Improving Communication Efficiencycited by 1,475
  4. 2017Federated Multi-Task Learningcited by 672
  5. 2020Ditto: Fair and Robust Federated Learning Through Personalizationcited by 672
  6. 2020An Efficient Framework for Clustered Federated Learningcited by 511
  7. 2019Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraintscited by 503
  8. 2020Federated Learning of a Mixture of Global and Local Modelscited by 210
  9. 2021Federated Multi-Task Learning under a Mixture of Distributionscited by 192
  10. 2016Decentralized Collaborative Learning of Personalized Models over Networkscited by 76
  11. 2022Collaborative Algorithms for Online Personalized Mean Estimationcited by 5
  12. 2024Scalable Decentralized Algorithms for Online Personalized Mean Estimationcited by 2
1 more
  1. 2024Differentially-Private Collaborative Online Personalized Mean Estimationcited by 1

Built on by

Not cited yet.