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cs.LG2021
Training Integrable Parameterizations of Deep Neural Networks in the Infinite-Width Limit
Karl Hajjar, Lénaïc Chizat, Christophe Giraud
To theoretically understand the behavior of trained deep neural networks, it is necessary to study the dynamics induced by gradient methods from a random initialization. However, t…
math.OC2021★ 3 cited
Convergence Rates of Gradient Methods for Convex Optimization in the Space of Measures
Lénaïc Chizat
We study the convergence rate of Bregman gradient methods for convex optimization in the space of measures on a -dimensional manifold. Under basic regularity assumptions, we sho…