2016
DOI: 10.1016/j.procs.2016.05.534
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A Riemannian Limited-Memory BFGS Algorithm for Computing the Matrix Geometric Mean

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Cited by 26 publications
(22 citation statements)
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“…Furthermore, Riemannian optimization offers a large panel of general optimization algorithms [24] and research on this topic is very active, see e.g. [51], [52]. Besides, we also provide a thorough study of the AJD problem of SPD matrices from an information geometry point of view subsuming previous research on this topic, and bringing new insights and original methods based on criteria that have not been considered before.…”
Section: Discussionmentioning
confidence: 98%
“…Furthermore, Riemannian optimization offers a large panel of general optimization algorithms [24] and research on this topic is very active, see e.g. [51], [52]. Besides, we also provide a thorough study of the AJD problem of SPD matrices from an information geometry point of view subsuming previous research on this topic, and bringing new insights and original methods based on criteria that have not been considered before.…”
Section: Discussionmentioning
confidence: 98%
“…A preliminary version of some of the results presented in this paper can be found in the conference paper by Yuan et al 28…”
Section: Contributionsmentioning
confidence: 99%
“…27 To the best of our knowledge, there is no other publicly available C++ toolbox for the SPD Karcher mean computation. Our previous work 28 provides a MATLAB implementation † for this problem. The Matrix Means Toolbox 25 developed by Bini et al 24 is also written in MATLAB.…”
Section: Contributionsmentioning
confidence: 99%
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