Abstract
Simplex Volume Maximization (SiVM) exploits distance geometry for efficiently factorizing gigantic matrices. It was proven successful in game, social media, and plant mining. Here, we review the distance geometry approach and argue that it generally suggests to factorize gigantic matrices using search-based instead of optimization techniques. © 2012 Springer-Verlag.
Cite
CITATION STYLE
Kersting, K., Bauckhage, C., Thurau, C., & Wahabzada, M. (2012). Matrix factorization as search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7524 LNAI, pp. 850–853). https://doi.org/10.1007/978-3-642-33486-3_62
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