Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization

Mikhail Persiianov, Arip Asadulaev, Nikita Andreev +5

Learning conditional distributions ${\pi }^{\ast }(\cdot |x)$ is a central problem in machine learning, which is typically approached via supervised methods with paired data $(x,y)\sim {\pi }^{\ast }$.…