Federated learning with heavy-tailed gradient noise and communication noise: a variance-reduction based algorithm

arXiv:2606.22466 · cs.LG, math.OC · Submitted 2026-06-21 · Read on arXiv

cs.LG, math.OC

Submitted: 2026-06-21

Updated: 2026-10-20

Terminology

• Federated Learning — 2× in this paper · explained in 17 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Federated Learning (FL) — 1× in this paper · explained in 11 episodes
• Heavy-Tailed Noise — 1× in this paper · explained in 3 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks