1 code implementation • 19 Jul 2023 • Guillaume Perez, Laurent Condat, Michel Barlaud
In this paper, we introduce a new projection algorithm for the $\ell_{1,\infty}$ norm ball.
no code implementations • 9 Sep 2022 • Cyprien Gille, Frédéric Guyard, Marc Antonini, Michel Barlaud
Recently, convolutional auto-encoders (CAE) were introduced for image coding.
1 code implementation • 22 Aug 2022 • Cyprien Gille, Frederic Guyard, Michel Barlaud
Experiments show that the SSAE outperforms Label Propagation and Spreading and the Fully Connected Neural Network both on a synthetic dataset and on two real-world biological datasets.
no code implementations • 7 Sep 2020 • Guillaume Perez, Sebastian Ament, Carla Gomes, Michel Barlaud
In this paper we propose three new efficient algorithms for projecting any vector of finite length onto the weighted $\ell_1$ ball.
no code implementations • 5 Feb 2019 • Michel Barlaud, Antonin Chambolle, Jean-Baptiste Caillau
This paper deals with supervised classification and feature selection in high dimensional space.
no code implementations • 8 Nov 2017 • Cyprien Gilet, Marie Deprez, Jean-Baptiste Caillau, Michel Barlaud
The projection-gradient step is a method of splitting type, with exact projection on the $\ell^1$ ball to promote sparsity.
1 code implementation • 23 Jun 2016 • Devis Tuia, Remi Flamary, Michel Barlaud
In this paper, we study the effect of different regularizers and their implications in high dimensional image classification and sparse linear unmixing.
no code implementations • 6 Jun 2015 • Michel Barlaud, Wafa Belhajali, Patrick L. Combettes, Lionel Fillatre
This paper deals with sparse feature selection and grouping for classification and regression.