Random sketch learning for deep neural networks in edge computing
- 25 March 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Computational Science
- Vol. 1 (3), 221-228
- https://doi.org/10.1038/s43588-021-00039-6
Abstract
No abstract availableKeywords
This publication has 30 references indexed in Scilit:
- TETRISPublished by Association for Computing Machinery (ACM) ,2017
- Mastering the game of Go with deep neural networks and tree searchNature, 2016
- Deep learningNature Methods, 2015
- Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark studyMechanical Systems and Signal Processing, 2015
- First-principles calculation of charged capacitors under open-circuit conditions using the orbital-separation approachPhysical Review B, 2015
- Deep learningNature, 2015
- Training and operation of an integrated neuromorphic network based on metal-oxide memristorsNature, 2015
- Speeding up Convolutional Neural Networks with Low Rank ExpansionsPublished by British Machine Vision Association and Society for Pattern Recognition ,2014
- On the potential of recording earthquakes for global seismic tomography by low‐cost autonomous instruments in the oceansJournal of Geophysical Research, 2009
- Relative-Error $CUR$ Matrix DecompositionsSIAM Journal on Matrix Analysis and Applications, 2008