{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/what-if-neural-networks-had-svds","title":"What if Neural Networks had SVDs?","arxiv_id":"2009.13977","date":"2020-09-29","proceeding":"NeurIPS 2020 12","authors":["Alexander Mathiasen","Frederik Hvilshøj","Jakob Rødsgaard Jørgensen","Anshul Nasery","Davide Mottin"],"abstract":"Various Neural Networks employ time-consuming matrix operations like matrix inversion. Many such matrix operations are faster to compute given the Singular Value Decomposition (SVD). Previous work allows using the SVD in Neural Networks without computing it. 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