Optimal data fitting on lie groups: A coset approach

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Abstract

This work considers the problem of fitting data on a Lie group by a coset of a compact subgroup. This problem can be seen as an extension of the problem of fitting affine subspaces in n to data which can be solved using principal component analysis. We show how the fitting problem can be reduced for biinvariant distances to a generalized mean calculation on an homogeneous space. For biinvariant Riemannian distances we provide an algorithm based on the Karcher mean gradient algorithm. We illustrate our approach by some examples on SO(n). © 2010 Springer -Verlag Berlin Heidelberg.

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Lageman, C., & Sepulchre, R. (2010). Optimal data fitting on lie groups: A coset approach. In Recent Advances in Optimization and its Applications in Engineering (pp. 173–182). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-12598-0_15

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