Structured Prediction with Sparse Wasserstein Barycenters

Explore a 49-minute lecture on structured prediction using sparse Wasserstein barycenters, presented by Olga Mula at the Institut Henri Poincaré in Paris. Delve into advanced mathematical concepts and their applications in machine learning and data analysis. Gain insights into the theory and practical implementation of Wasserstein barycenters for solving complex prediction problems. Learn how sparsity constraints can be leveraged to improve computational efficiency and interpretability in structured prediction tasks. Discover the latest research developments in this field and their potential impact on various domains such as computer vision, natural language processing, and statistical learning.