1 citations · 1 across the 8 of their papers we have counts for
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Learning Theory for Kernel Bilevel Optimization
Fares El Khoury, Edouard Pauwels, Samuel Vaiter +1
Bilevel optimization has emerged as a technique for addressing a wide range of machine learning problems that involve an outer objective implicitly determined by the minimizer of a…
A second-order-like optimizer with adaptive gradient scaling for deep learning
Jérôme Bolte, Ryan Boustany, Edouard Pauwels +1
In this empirical article, we introduce INNAprop, an optimization algorithm that combines the INNA method with the RMSprop adaptive gradient scaling. It leverages second-order info…
Numerical influence of ReLU'(0) on backpropagation
David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz +1
In theory, the choice of ReLU(0) in [0, 1] for a neural network has a negligible influence both on backpropagation and training. Yet, in the real world, 32 bits default precision c…