355 citations · 1.6k across the 54 of their papers we have counts for
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stat.ML2022★ 1 cited
Iterative regularization in classification via hinge loss diagonal descent
Vassilis Apidopoulos, Tomaso Poggio, Lorenzo Rosasco +1
Iterative regularization is a classic idea in regularization theory, that has recently become popular in machine learning. On the one hand, it allows to design efficient algorithms…
cs.LG2022★ 1 cited
SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network
Tomer Galanti, Zachary S. Siegel, Aparna Gupte +1
We investigate the inherent bias of Stochastic Gradient Descent (SGD) toward learning low-rank weight matrices during the training of deep neural networks. Our results demonstrate…