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Riemannian Online Algorithms for Estimating Mixture Model Parameters

Abstract : This paper introduces a novel algorithm for the online estimate of the Riemannian mixture model parameters. This new approach counts on Riemannian geometry concepts to extend the well-known Tit-terington approach for the online estimate of mixture model parameters in the Euclidean case to the Riemannian manifolds. Here, Riemannian mixtures in the Riemannian manifold of Symmetric Positive Definite (SPD) matrices are analyzed in details, even if the method is well suited for other manifolds.
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https://hal.archives-ouvertes.fr/hal-01630177
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Submitted on : Tuesday, November 7, 2017 - 11:54:05 AM
Last modification on : Wednesday, November 3, 2021 - 5:09:08 AM
Long-term archiving on: : Thursday, February 8, 2018 - 2:02:07 PM

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Paolo Zanini, Salem Said, Yannick Berthoumieu, Marco Congedo, Christian Jutten. Riemannian Online Algorithms for Estimating Mixture Model Parameters. Geometric Science of Information (GSI 2017), Nov 2017, Paris, France. ⟨10.1007/978-3-319-68445-1_78⟩. ⟨hal-01630177⟩

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