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Towards Discovering Neural Architectures from Scratch. (arXiv:2211.01842v1 [cs.LG])
Nov. 4, 2022, 1:13 a.m. | Simon Schrodi, Danny Stoll, Binxin Ru, Rhea Sukthanker, Thomas Brox, Frank Hutter
stat.ML updates on arXiv.org arxiv.org
The discovery of neural architectures from scratch is the long-standing goal
of Neural Architecture Search (NAS). Searching over a wide spectrum of neural
architectures can facilitate the discovery of previously unconsidered but
well-performing architectures. In this work, we take a large step towards
discovering neural architectures from scratch by expressing architectures
algebraically. This algebraic view leads to a more general method for designing
search spaces, which allows us to compactly represent search spaces that are
100s of orders of magnitude …
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