A Peer-Relative Representation Learning Framework for Energy Inefficiency Identification in Mobile Network Sites

arXiv:2609.03809 · cs.LG · Submitted 2026-09-03 · Read on arXiv

cs.LG

Submitted: 2026-09-03

Updated: 2026-09-03

Comments: 22 pages, 6 figures

Code: https://github.com/eliud-koto/peer-relative-energy-aware-mde

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

Terminology

• AUC — 28× in this paper · explained in 2 episodes
• Representation Learning — 7× in this paper · explained in 2 episodes
• Distillation — 6× in this paper · explained in 2 episodes
• Graph Construction — 6× in this paper · explained in 3 episodes
• Pseudo-labels — 6× in this paper · explained in 2 episodes
• Energy Efficiency — 4× in this paper · explained in 3 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• African Institute for Mathematical Sciences — 1× in this paper
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Gaussian Mixture Model (GMM) — 1× in this paper · explained in 2 episodes
• IEEE International Conference on Data Mining — 1× in this paper
• Interpretability — 1× in this paper · explained in 15 episodes
• Minimum Distortion Embedding — 1× in this paper
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes
• Verification — 1× in this paper · explained in 2 episodes

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