Hamiltonian Monte-Carlo for Orthogonal Matrices

We consider the problem of sampling from posterior distributions for Bayesian models where some parameters are restricted to be orthogonal matrices. Such matrices are sometimes used in neural networks models for reasons of regularization and stabilization of training procedures, and also can paramet...

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Bibliographische Detailangaben

Hauptverfasser:	Yanush, Viktor, Kropotov, Dmitry
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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