3 papers
cs.LG2026
Scale When Needed: Adaptive Neuron-level Mixed Precision Quantization Aware Training
Ayush K. Varshney, Konstantinos Vandikas, Šarūnas Girdzijauskas +2
Deploying deep neural networks on resource-constrained 6G edge devices demands aggressive compression with minimal accuracy loss. Quantization-Aware Training (QAT) has emerged as a…
cs.LG2026
Automated Model Design using Gated Neuron Selection in Telecom
Adam Orucu, Marcus Medhage, Farnaz Moradi +2
The telecommunications industry is experiencing rapid growth in adopting deep learning for critical tasks such as traffic prediction, signal strength prediction, and quality of ser…
cs.NI2024
Towards Neural Architecture Search for Transfer Learning in 6G Networks
Adam Orucu, Farnaz Moradi, Masoumeh Ebrahimi +1
The future 6G network is envisioned to be AI-native, and as such, ML models will be pervasive in support of optimizing performance, reducing energy consumption, and in coping with…