Designing neural networks that are both accurate and efficient has become an urgent challenge as the cost of deploying machine learning systems continues to grow. Traditional Neural Architecture Search (NAS) methods usually optimize for accuracy under constraints such as FLOPs, model size, or latency. However, in practice the lifecycle cost of a model is not only determined by training, but also …
Supervisors: Pınar Tözün, Ehsan Yousefzadeh-Asl-Miandoab
Semester: Fall 2025
Tags: machine learning, Green AI, energy usage, NAS