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Matrix Factorization as Search

Kristian Kersting; Christian Bauckhage; Christian Thurau; Mirwaes Wahabzada
In: Peter A. Flach; Tijl De Bie; Nello Cristianini (Hrsg.). Machine Learning and Knowledge Discovery in Databases - European Conference. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD-2012), September 24-28, Bristol, United Kingdom, Pages 850-853, Lecture Notes in Computer Science, Vol. 7524, Springer, 2012.


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.

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