Federated Personalization of Early-Exit Networks

arXiv:2601.10015 · cs.LG · Submitted 2026-01-15 · Read on arXiv

cs.LG

Submitted: 2026-01-15

Updated: 2026-08-29

Comments: 12 pages, conference

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

Terminology

• Accuracy — 73× in this paper · explained in 1 episode
• Distillation — 45× in this paper · explained in 2 episodes
• Federated Learning — 41× in this paper · explained in 14 episodes
• Personalized Federated Learning — 19× in this paper
• Aggregation — 11× in this paper · explained in 1 episode
• Personalization — 8× in this paper · explained in 2 episodes
• Knowledge Distillation — 7× in this paper · explained in 11 episodes
• Communication Overhead — 6× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Data Heterogeneity — 3× in this paper · explained in 3 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Non-IID Data — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Adversarial Training — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Federated Learning with Personalization Layers
• A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets
• Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification
• FedMD: Heterogenous Federated Learning via Model Distillation

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