35 citations · 81 across the 22 of their papers we have counts for
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cs.LG2021★ 3 cited
Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity
Scott Pesme, Loucas Pillaud-Vivien, Nicolas Flammarion
Understanding the implicit bias of training algorithms is of crucial importance in order to explain the success of overparametrised neural networks. In this paper, we study the dyn…
cs.LG2021★ 6 cited
Last iterate convergence of SGD for Least-Squares in the Interpolation regime
Aditya Varre, Loucas Pillaud-Vivien, Nicolas Flammarion
Motivated by the recent successes of neural networks that have the ability to fit the data perfectly and generalize well, we study the noiseless model in the fundamental least-squa…