RoME-QCD: Robust and Measurement Efficient Quickest Change Detection in 5G Networks

S Lindståhl, A Proutiere… - 2024 8th Network Traffic …, 2024 - ieeexplore.ieee.org
To effectively monitor a network and verify its performance, it is essential to quickly detect
sudden changes in its state, even when the form of such a change is initially unknown. While …

On Multi-Objective Neural Architecture Search for Modeling Network Performance

A Orucu, F Moradi, M Ebrahimi… - 2024 15th International …, 2024 - ieeexplore.ieee.org
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 co** …

Self-supervised Pretraining for User Performance Prediction under Scarce Data Conditions

A Rao, M Boman - Authorea Preprints, 2025 - techrxiv.org
Predicting user performance at the base station in telecom networks is a critical task that can
significantly benefit from advanced machine learning techniques. However, labeled data for …

[HTML][HTML] Transfer Learning and Domain Adaptation in Telecommunications

K Vandikas, F Moradi, H Larsson, A Johnsson - 2024 - intechopen.com
Transfer learning (TL) and domain adaptation (DA) are well-known approaches in the AI
literature that can be used to address the fundamental challenge of data scarcity. TL and DA …