Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters

1 code implementation • 2 Feb 2022 • Johannes von Lindheim

While entropic regularization has been successfully applied to approximate Wasserstein barycenters, this loses the sparsity of the optimal solution, making it difficult to solve the MOT problem directly in practice because of the curse of dimensionality.

The Oracle of DLphi

no code implementations • 17 Jan 2019 • Dominik Alfke, Weston Baines, Jan Blechschmidt, Mauricio J. del Razo Sarmina, Amnon Drory, Dennis Elbrächter, Nando Farchmin, Matteo Gambara, Silke Glas, Philipp Grohs, Peter Hinz, Danijel Kivaranovic, Christian Kümmerle, Gitta Kutyniok, Sebastian Lunz, Jan Macdonald, Ryan Malthaner, Gregory Naisat, Ariel Neufeld, Philipp Christian Petersen, Rafael Reisenhofer, Jun-Da Sheng, Laura Thesing, Philipp Trunschke, Johannes von Lindheim, David Weber, Melanie Weber

We present a novel technique based on deep learning and set theory which yields exceptional classification and prediction results.

General Classification

On Hyperparameter Search in Cluster Ensembles

no code implementations • 29 Mar 2018 • Luzie Helfmann, Johannes von Lindheim, Mattes Mollenhauer, Ralf Banisch

Quality assessments of models in unsupervised learning and clustering verification in particular have been a long-standing problem in the machine learning research.

Clustering Clustering Ensemble