Optimal Transport with Adaptive Regularisation

no code implementations • 4 Oct 2023 • Hugues van Assel, Titouan Vayer, Remi Flamary, Nicolas Courty

Regularising the primal formulation of optimal transport (OT) with a strictly convex term leads to enhanced numerical complexity and a denser transport plan.

Domain Adaptation

Contextual Semantic Interpretability

1 code implementation • 18 Sep 2020 • Diego Marcos, Ruth Fong, Sylvain Lobry, Remi Flamary, Nicolas Courty, Devis Tuia

Once the attributes are learned, they can be re-combined to reach the final decision and provide both an accurate prediction and an explicit reasoning behind the CNN decision.

Large Scale Optimal Transport and Mapping Estimation

no code implementations • ICLR 2018 • Vivien Seguy, Bharath Bhushan Damodaran, Remi Flamary, Nicolas Courty, Antoine Rolet, Mathieu Blondel

First, we learn an optimal transport (OT) plan, which can be thought as a one-to-many map between the two distributions.

Domain Adaptation

Non-convex regularization in remote sensing

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.

Classification General Classification +1

DC Proximal Newton for Non-Convex Optimization Problems

no code implementations • 2 Jul 2015 • Alain Rakotomamonjy, Remi Flamary, Gilles Gasso

We introduce a novel algorithm for solving learning problems where both the loss function and the regularizer are non-convex but belong to the class of difference of convex (DC) functions.

Transductive Learning