Dec 1, 2021 · This paper establishes some conditions under which the Wasserstein distance can be controlled by MMD norms.
This paper estab- lishes some conditions under which the Wasserstein distance can be controlled by MMD norms. Our work is motivated by the compressive ...
Mar 6, 2024 · Our work is motivated by the compressive statistical learning (CSL) theory, a general framework for resource-efficient large scale learning in ...
This paper establishes some conditions under which the Wasserstein distance can be controlled by MMD norms, and introduces the Holder Lower Restricted ...
[PDF] Controlling Wasserstein distances by Kernel norms with application ... - HAL
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Dec 1, 2021 · This study is motivated by the compressive statistical learning (CSL) framework whose aim is to provide resource efficient large-scale learning ...
The present study asked the question whether forward and backward blocking occur during visual statistical learning, i.e., the incidental learning of the ...
Jun 8, 2023 · 'Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning', by Titouan Vayer, Rémi Gribonval.
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Sep 4, 2023 · Using Kernel Norms to Control Wasserstein Distances and its Application in Compressive Statistical Learning Controlling Wasserstein Distances ...
Transactions on Machine Learning Research, 2022. 13, 2022. Controlling Wasserstein distances by Kernel norms with application to Compressive Statistical ...
Controlling Wasserstein distances by Kernel norms with application to Compressive Statistical Learning. T Vayer, R Gribonval. Journal of Machine Learning ...