In this paper, we tackle the problem of reducing discrepancies between multiple domains, i.e. multi-source domain adaptation, and consider it under the target shift assumption: in all domains we aim to solve a classification problem with the same output classes, but with different labels proportions. This problem , generally ignored in the vast...
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April 16, 2019 (v1)Conference paperUploaded on: December 4, 2022
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April 1, 2021 (v1)Journal article
Optimal transport has recently been reintroduced to the machine learning community thanks in part to novel efficient optimization procedures allowing for medium to large scale applications. We propose a Python toolbox that implements several key optimal transport ideas for the machine learning community. The toolbox contains implementations of...
Uploaded on: December 4, 2022