Pareto Rank Surrogate Model for Hardware-aware Neural Architecture Search

Author:

Benmeziane Hadjer1,Niar Smail1,Ouarnoughi Hamza1,Maghraoui Kaoutar El2

Affiliation:

1. Université Polytechnique Hauts-de-France,LAMIH UMR CNRS,Valenciennes,France

2. IBM T. J. Watson Research Center,NY,USA

Publisher

IEEE

Reference26 articles.

1. Nas-bench-201: Extending the scope of reproducible neural architecture search;dong;ICLR International Conference on Learning Representations,2020

2. A generic graphbased neural architecture encoding scheme for predictor-based NAS;ning;Computer Vision - ECCV - 16th European Conference ser Lecture Notes in Computer Science,2020

3. Learning to rank learning curves;wistuba;Proceedings of the 37th International Conference on Machine Learning ser Proceedings of Machine Learning Research,2020

4. A comprehensive survey on hardware-aware neural architecture search;benmeziane;CoRR,2021

5. A survey on learning to rank;he;International Conference on Machine Learning and Cybernetics,2008

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