353 citations · 491 across the 14 of their papers we have counts for
5 papers · 1 filter
Lloyd's -Means Clustering Algorithm Is Frank-Wolfe in Disguise
Michael Pokojovy, J. Marcus Jobe, Simon Lacoste-Julien
Lloyd's -means algorithm, also known as naïve -means, is a widely used ad hoc optimization heuristic, designed to minimize the sum of squared errors (SSE) across all -part…
An Analysis of the Adaptation Speed of Causal Models
Rémi Le Priol, Reza Babanezhad Harikandeh, Yoshua Bengio +1
Consider a collection of datasets generated by unknown interventions on an unknown structural causal model . Recently, Bengio et al. (2020) conjectured that among all candidate…
Reducing Noise in GAN Training with Variance Reduced Extragradient
Tatjana Chavdarova, Gauthier Gidel, François Fleuret +1
We study the effect of the stochastic gradient noise on the training of generative adversarial networks (GANs) and show that it can prevent the convergence of standard game optimiz…
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…
Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering
Simon Lacoste-Julien, Fredrik Lindsten, Francis Bach
Recently, the Frank-Wolfe optimization algorithm was suggested as a procedure to obtain adaptive quadrature rules for integrals of functions in a reproducing kernel Hilbert space (…