Multi-Fidelity Neural Architecture Search With Knowledge Distillation

Multi-Fidelity Neural Architecture Search With Knowledge Distillation

Neural architecture search (NAS) targets at finding the optimal architecture of a neural network for a problem or a family of problems. Evaluations of neural architectures are very time-consuming. One of the possible ways to mitigate this issue is to use low-fidelity evaluations, namely training on...

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Bibliographic Details
Main Authors: Ilya Trofimov, Nikita Klyuchnikov, Mikhail Salnikov, Alexander Filippov, Evgeny Burnaev
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Bayesian optimization
knowledge distillation
multi-fidelity optimization
neural architecture search
Online Access:https://ieeexplore.ieee.org/document/10007805/

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