5 citations · 13 across the 6 of their papers we have counts for
12 papers
Efficient Online-Bandit Strategies for Minimax Learning Problems
Christophe Roux, Elias Wirth, Sebastian Pokutta +1
Several learning problems involve solving min-max problems, e.g., empirical distributional robust learning or learning with non-standard aggregated losses. More specifically, these…
Linear Bandits on Uniformly Convex Sets
Thomas Kerdreux, Christophe Roux, Alexandre d'Aspremont +1
Linear bandit algorithms yield pseudo-regret bounds on compact convex action sets and two types of structural assu…
Local and Global Uniform Convexity Conditions
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
We review various characterizations of uniform convexity and smoothness on norm balls in finite-dimensional spaces and connect results stemming from the geometry of Banach spaces w…
Generating Structured Adversarial Attacks Using Frank-Wolfe Method
Ehsan Kazemi, Thomas Kerdreux, Liquang Wang
White box adversarial perturbations are generated via iterative optimization algorithms most often by minimizing an adversarial loss on a neighborhood of the original imag…
Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets
Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien +1
It is known that the Frank-Wolfe (FW) algorithm, which is affine-covariant, enjoys accelerated convergence rates when the constraint set is strongly convex. However, these results…
Diptychs of human and machine perceptions
Vivien Cabannes, Thomas Kerdreux, Louis Thiry
We propose visual creations that put differences in algorithms and humans \emph{perceptions} into perspective. We exploit saliency maps of neural networks and visual focus of human…