Alleviating Label Switching with Optimal Transport

NeurIPS 2019 Pierre MonteillerSebastian ClaiciEdward ChienFarzaneh MirzazadehJustin SolomonMikhail Yurochkin

Label switching is a phenomenon arising in mixture model posterior inference that prevents one from meaningfully assessing posterior statistics using standard Monte Carlo procedures. This issue arises due to invariance of the posterior under actions of a group; for example, permuting the ordering of mixture components has no effect on the likelihood... (read more)

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