Self-induced regularization from linear regression to neural networks
https://youtu.be/bjRqmlI_SFs Speaker: Andrea Montanari, Departments of Electrical Engineering and Statistics, Stanford Title: Self-induced regularization from linear regression to neural networks Abstract: Modern machine learning methods --most noticeably multi-layer neural networks-- require to fit highly non-linear models comprising tens of thousands to millions of parameters. Despite this, little attention is paid to the regularization mechanism to […]