1 code implementation • 31 Aug 2023 • Alexandre Tuel, Thomas Kerdreux, Claudia Hulbert, Bertrand Rouet-Leduc
Probabilistic Diffusion Models (PDMs) have recently emerged as a very promising class of generative models, achieving high performance in natural image generation.
no code implementations • 21 Aug 2023 • Bertrand Rouet-Leduc, Thomas Kerdreux, Alexandre Tuel, Claudia Hulbert
Methane is one of the most potent greenhouse gases, and its short atmospheric half-life makes it a prime target to rapidly curb global warming.
no code implementations • 28 May 2021 • Christophe Roux, Elias Wirth, Sebastian Pokutta, Thomas Kerdreux
Several learning problems involve solving min-max problems, e. g., empirical distributional robust learning or learning with non-standard aggregated losses.
no code implementations • 10 Mar 2021 • Thomas Kerdreux, Christophe Roux, Alexandre d'Aspremont, Sebastian Pokutta
Linear bandit algorithms yield $\tilde{\mathcal{O}}(n\sqrt{T})$ pseudo-regret bounds on compact convex action sets $\mathcal{K}\subset\mathbb{R}^n$ and two types of structural assumptions lead to better pseudo-regret bounds.
no code implementations • 15 Feb 2021 • 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 $\ell_p$ neighborhood of the original image, the so-called distortion set.
no code implementations • 9 Feb 2021 • 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 with \textit{scaling inequalities} used in analysing the convergence of optimization methods.
no code implementations • 12 Oct 2020 • Vivien Cabannes, Thomas Kerdreux, Louis Thiry
We propose visual creations that put differences in algorithms and humans \emph{perceptions} into perspective.
no code implementations • 2 Jul 2020 • Ehsan Kazemi, Thomas Kerdreux, Liqiang Wang
White box adversarial perturbations are sought via iterative optimization algorithms most often minimizing an adversarial loss on a $l_p$ neighborhood of the original image, the so-called distortion set.
1 code implementation • 14 Mar 2020 • Thomas Kerdreux, Louis Thiry, Erwan Kerdreux
We present interactive painting processes in which a painter and various neural style transfer algorithms interact on a real canvas.
no code implementations • 10 Oct 2019 • Vivien Cabannes, Thomas Kerdreux, Louis Thiry, Tina Campana, Charly Ferrandes
We propose a new form of human-machine interaction.
1 code implementation • 18 Jul 2018 • Antoine Recanati, Thomas Kerdreux, Alexandre d'Aspremont
We tackle the task of retrieving linear and circular orderings in a unifying framework, and show how a latent ordering on the data translates into a filamentary structure on the Laplacian embedding.
Data Structures and Algorithms Genomics
no code implementations • ICML 2018 • Thomas Kerdreux, Fabian Pedregosa, Alexandre d'Aspremont
The first algorithm that we propose is a randomized variant of the original FW algorithm and achieves a $\mathcal{O}(1/t)$ sublinear convergence rate as in the deterministic counterpart.