SAGE: Optimal-Stopping Peer Selection for Decentralised Federated Learning

arXiv:2609.23773 · cs.DC, cs.LG · Submitted 2026-09-20 · Read on arXiv

cs.DC, cs.LG

Submitted: 2026-09-20

Updated: 2026-09-20

Comments: 12 pages, 3 figures, 3 tables

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

Terminology

Accuracy — 31× in this paper · explained in 1 episode
Federated Learning — 25× in this paper · explained in 15 episodes
Abstention — 6× in this paper · explained in 1 episode
Aggregation — 4× in this paper · explained in 1 episode
Decentralized Federated Learning — 4× in this paper · explained in 2 episodes
Ablation — 3× in this paper · explained in 1 episode
Communication Overhead — 3× in this paper · explained in 2 episodes
Differential Privacy — 3× in this paper · explained in 4 episodes
Distillation — 3× in this paper · explained in 2 episodes
Anchor Loss — 2× in this paper · explained in 1 episode
Benchmark — 2× in this paper · explained in 2 episodes
Non-IID Data — 2× in this paper · explained in 2 episodes
Adam — 1× in this paper · explained in 2 episodes
Adaptive Selection — 1× in this paper · explained in 1 episode
Adaptivity — 1× in this paper · explained in 1 episode
Cooperation — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Energy Efficiency — 1× in this paper · explained in 3 episodes
Knowledge Distillation — 1× in this paper · explained in 11 episodes
Latent Representation — 1× in this paper · explained in 2 episodes
Reinforcement Learning — 1× in this paper · explained in 4 episodes
Sample Complexity — 1× in this paper · explained in 15 episodes
Sequential Anchor-Gated Exchange — 1× in this paper

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