Search Results for author: Julien Fageot

Found 8 papers, 4 papers with code

A Decoupled Approach for Composite Sparse-plus-Smooth Penalized Optimization

1 code implementation8 Mar 2024 Adrian Jarret, Valérie Costa, Julien Fageot

Consequently, we identify that solving the optimization problem can be decoupled, first identifying the sparse solution as a solution of a modified single-variable problem, then deducing the smooth component.

Une version polyatomique de l'algorithme Frank-Wolfe pour résoudre le problème LASSO en grandes dimensions

no code implementations28 Apr 2022 Adrian Jarret, Matthieu Simeoni, Julien Fageot

Nous d\'emontrons sa sup\'eriorit\'e par rapport aux m\'ethodes proximales dans des situations en grande dimension avec des mesures de Fourier, lors de la r\'esolution de probl\`emes simul\'es inspir\'es de la radio-interf\'erom\'etrie.

Astronomy Radio Interferometry

A Fast and Scalable Polyatomic Frank-Wolfe Algorithm for the LASSO

1 code implementation6 Dec 2021 Adrian Jarret, Julien Fageot, Matthieu Simeoni

We propose a fast and scalable Polyatomic Frank-Wolfe (P-FW) algorithm for the resolution of high-dimensional LASSO regression problems.

Efficient Exploration

3D Solid Spherical Bispectrum CNNs for Biomedical Texture Analysis

1 code implementation28 Apr 2020 Valentin Oreiller, Vincent Andrearczyk, Julien Fageot, John O. Prior, Adrien Depeursinge

We investigate the benefits of using the bispectrum over the spectrum in the design of a LRI layer embedded in a shallow Convolutional Neural Network (CNN) for 3D image analysis.

Computed Tomography (CT) Texture Classification

Local Rotation Invariance in 3D CNNs

1 code implementation19 Mar 2020 Vincent Andrearczyk, Julien Fageot, Valentin Oreiller, Xavier Montet, Adrien Depeursinge

Locally Rotation Invariant (LRI) image analysis was shown to be fundamental in many applications and in particular in medical imaging where local structures of tissues occur at arbitrary rotations.

Data Augmentation Texture Classification

Native Banach spaces for splines and variational inverse problems

no code implementations24 Apr 2019 Michael Unser, Julien Fageot

In short, the native space for ${\rm L}$ and the (dual) norm $\|\cdot\|_{\mathcal{X}'}$ is the largest space of functions $f: \mathbb{R}^d \to \mathbb{R}$ such that $\|{\rm L} f\|_{\mathcal{X}'}<\infty$, subject to the constraint that the growth-restricted null space of ${\rm L}$be finite-dimensional.

The Domain of Definition of the Lévy White Noise

no code implementations8 Aug 2017 Julien Fageot, Thomas Humeau

It is possible to construct L\'evy white noises as generalized random processes in the sense of Gel'fand and Vilenkin, or as an independently scattered random measures introduced by Rajput and Rosinski.

Probability 60G20, 60G57, 60G51, 60H15, 60H40

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