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Abstract: In various applications, data in multi-dimensional space are normalized to unit length. This paper considers the problem of best fitting given points on the m-dimensional unit sphere S by k-dimensional great circles with k much less than m. The task is cast as an algebraically constrained low-rank matrix approximation problem. Using the fidelity of the low-rank approximation to the original data as the cost function, this paper o#ers an analytic expression of the projected gradient which, on ... (Update)
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BibTeX entry: (Update)
@misc{ buono-lowrank,
author = "Chu Del Buono",
title = "On The Low-Rank Approximation Of Data On The Unit Sphere",
url = "citeseer.ist.psu.edu/757158.html" }
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