Joint Optimization for Federated Learning and Transmission over Unreliable Wireless Networks with Heterogeneous Data

arXiv:2609.14246 · cs.DC, cs.LG · Submitted 2026-09-13 · Read on arXiv

cs.DC, cs.LG

Submitted: 2026-09-13

Updated: 2026-09-13

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

Terminology

• Accuracy — 44× in this paper · explained in 1 episode
• Federated Learning — 33× in this paper · explained in 15 episodes
• Aggregation — 25× in this paper · explained in 1 episode
• Data Heterogeneity — 22× in this paper · explained in 3 episodes
• Pruning — 9× in this paper · explained in 4 episodes
• Communication Overhead — 8× in this paper · explained in 2 episodes
• Non-IID Data — 6× in this paper · explained in 2 episodes
• Core — 5× in this paper · explained in 2 episodes
• Clustering — 4× in this paper · explained in 2 episodes
• Convergence Guarantees — 4× in this paper · explained in 3 episodes
• Redundancy — 4× in this paper · explained in 2 episodes
• Meta-learning — 3× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Energy Efficiency — 2× in this paper · explained in 3 episodes
• Federated Learning (FL) — 2× in this paper · explained in 7 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Decentralized Federated Learning — 1× in this paper · explained in 2 episodes
• Decentralized Learning — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Differential Privacy — 1× in this paper · explained in 4 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Homogenization — 1× in this paper · explained in 2 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Lyapunov function — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Signal-to-noise ratio (SNR) — 1× in this paper · explained in 2 episodes
• Stochastic Gradient Descent (SGD) — 1× in this paper · explained in 5 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Sources

• Federated Meta-Learning with Fast Convergence and Efficient Communication
• Very Deep Convolutional Networks for Large-Scale Image Recognition

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