Institut de Mathématiques de Marseille, UMR 7373


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Optimal transport for machine learning

Vendredi 19 janvier 14:00-15:00 - Rémi FLAMARY - Université de Nice Sophia-Antipolis

Optimal transport for machine learning

Résumé : First we present a brief introduction to optimal transport and to the Wasserstein distance. Next we will discuss recent applications of OT in Machine Learning. OT can be used to estimate a mapping between distributions for color adaptation between images and domain adaptation. But it is also a very powerful data fitting term for learning with histograms or empirical distributions for classification, audio spectral unmixing and Generative Adversarial networks.

PNG - 46.6 ko

Lieu : CMI, salle de séminaire R164 (1er étage) - I2M - Château-Gombert
39 rue Frédéric Joliot-Curie
13453 Marseille cedex 13

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Pour en savoir plus sur cet événement, consultez l'article Séminaire Signal et Apprentissage