353 citations · 1.3k across the 38 of their papers we have counts for
3 papers · 1 filter
Three Factors Influencing Minima in SGD
Stanisław Jastrzębski, Zachary Kenton, Devansh Arpit +4
We investigate the dynamical and convergent properties of stochastic gradient descent (SGD) applied to Deep Neural Networks (DNNs). Characterizing the relation between learning rat…
On the regularization of Wasserstein GANs
Henning Petzka, Asja Fischer, Denis Lukovnikov
Since their invention, generative adversarial networks (GANs) have become a popular approach for learning to model a distribution of real (unlabeled) data. Convergence problems dur…
A Closer Look at Memorization in Deep Networks
Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas +8
We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness. While deep networks are capable of memorizing noi…