A Large-Dimensional Analysis of Least-Squares Federated Learning via Generalized Total Variation Minimization

arXiv:2610.20075 · cs.LG, stat.ML · Submitted 2026-10-14 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-10-14

Updated: 2026-10-14

Comments: 21 pages, 9 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Federated Learning — 1× in this paper · explained in 17 episodes

Sources

• Federated Learning of a Mixture of Global and Local Models
• Federated Learning: From Theory to Practice
• Concentration of Measure and Large Random Matrices with an application to Sample Covariance Matrices
• High Dimensional Classification via Regularized and Unregularized Empirical Risk Minimization: Precise Error and Optimal Loss
• Three Approaches for Personalization with Applications to Federated Learning
• Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

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