April 4, 2024, 4:41 a.m. | Rob Geada, David Towers, Matthew Forshaw, Amir Atapour-Abarghouei, A. Stephen McGough

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.02189v1 Announce Type: new
Abstract: The boundless possibility of neural networks which can be used to solve a problem -- each with different performance -- leads to a situation where a Deep Learning expert is required to identify the best neural network. This goes against the hope of removing the need for experts. Neural Architecture Search (NAS) offers a solution to this by automatically identifying the best architecture. However, to date, NAS work has focused on a small set of …

abstract architecture arxiv cs.ai cs.cv cs.lg datasets deep learning expert identify insights leads network networks neural architecture search neural network neural networks performance possibility search solve type

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Associate Data Engineer

@ Nominet | Oxford/ Hybrid, GB

Data Science Senior Associate

@ JPMorgan Chase & Co. | Bengaluru, Karnataka, India