A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport
Kernel-based optimal transport (OT) estimators offer an alternative, functional estimation procedure to address OT problems from samples. Recent works suggest that these estimators are more statistically efficient than plug-in (linear programming-based) OT estimators when comparing probability measures in high-dimensions [Vacher et al., 2021]. Unfortunately, that statistical benefit comes at a very steep...
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Kernel-based optimal transport (OT) estimators offer an alternative, functional estimation procedure to address OT problems from samples. Recent works suggest that these estimators are more statistically efficient than plug-in (linear programming-based) OT estimators when comparing probability measures in high-dimensions [Vacher et al., 2021]. Unfortunately, that statistical benefit comes at a very steep...
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- Apple Machine Learning ResearchSource primaire · Confirme · EN · 100%A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport ↗
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