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cs.LG2022★ 4 cited
SGD with Large Step Sizes Learns Sparse Features
Maksym Andriushchenko, Aditya Varre, Loucas Pillaud-Vivien +1
We showcase important features of the dynamics of the Stochastic Gradient Descent (SGD) in the training of neural networks. We present empirical observations that commonly used lar…
cs.LG2022
Accelerated SGD for Non-Strongly-Convex Least Squares
Aditya Varre, Nicolas Flammarion
We consider stochastic approximation for the least squares regression problem in the non-strongly convex setting. We present the first practical algorithm that achieves the optimal…