Open AccessAutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks
Author(s) -
Youngmin Ro,
Jin Young Choi
Publication year - 2021
Publication title -
proceedings of the aaai conference on artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2374-3468
pISSN - 2159-5399
DOI - 10.1609/aaai.v35i3.16350
Subject(s) - benchmark (surveying) , pruning , computer science , layer (electronics) , code (set theory) , fine tuning , artificial intelligence , deep learning , machine learning , product (mathematics) , pattern recognition (psychology) , mathematics , set (abstract data type) , materials science , physics , geometry , geodesy , quantum mechanics , agronomy , composite material , biology , programming language , geography
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