Unified Robust and Convergent Over-The-Air Federated Learning under Channel Noise and Heterogeneity

arXiv:2503.19549 · cs.LG, eess.SP · Submitted 2025-03-25 · Read on arXiv

cs.LG, eess.SP

Submitted: 2025-03-25

Updated: 2026-10-26

Terminology

• Federated Learning — 4× in this paper · explained in 18 episodes
• Robustness — 2× in this paper · explained in 6 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Federated Learning (FL) — 1× in this paper · explained in 12 episodes
• Local Optimization — 1× in this paper · explained in 2 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