72 citations · 191 across the 22 of their papers we have counts for
9 papers · 1 filter
Gaussian-Smoothed Sliced Probability Divergences
Mokhtar Z. Alaya, Alain Rakotomamonjy, Maxime Berar +1
Gaussian smoothed sliced Wasserstein distance has been recently introduced for comparing probability distributions, while preserving privacy on the data. It has been shown that it…
Statistical and Topological Properties of Gaussian Smoothed Sliced Probability Divergences
Alain Rakotomamonjy, Mokhtar Z. Alaya, Maxime Berar +1
Gaussian smoothed sliced Wasserstein distance has been recently introduced for comparing probability distributions, while preserving privacy on the data. It has been shown, in appl…
Heterogeneous Wasserstein Discrepancy for Incomparable Distributions
Mokhtar Z. Alaya, Gilles Gasso, Maxime Berar +1
Optimal Transport (OT) metrics allow for defining discrepancies between two probability measures. Wasserstein distance is for longer the celebrated OT-distance frequently-used in t…
Open Set Domain Adaptation using Optimal Transport
Marwa Kechaou, Romain Hérault, Mokhtar Z. Alaya +1
We present a 2-step optimal transport approach that performs a mapping from a source distribution to a target distribution. Here, the target has the particularity to present new cl…
Optimal Transport for Conditional Domain Matching and Label Shift
Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso +3
We address the problem of unsupervised domain adaptation under the setting of generalized target shift (joint class-conditional and label shifts). For this framework, we theoretica…
Screening Rules for Lasso with Non-Convex Sparse Regularizers
Alain Rakotomamonjy, Gilles Gasso, Joseph Salmon
Leveraging on the convexity of the Lasso problem , screening rules help in accelerating solvers by discarding irrelevant variables, during the optimization process. However, becaus…