Projection techniques to update the truncated SVD of evolving matrices

no code implementations • 13 Oct 2020 • Vassilis Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, Lior Horesh, Kenneth L. Clarkson

This paper considers the problem of updating the rank-k truncated Singular Value Decomposition (SVD) of matrices subject to the addition of new rows and/or columns over time.

Recommendation Systems

EigenRec: Generalizing PureSVD for Effective and Efficient Top-N Recommendations

1 code implementation • 19 Nov 2015 • Athanasios N. Nikolakopoulos, Vassilis Kalantzis, Efstratios Gallopoulos, John D. Garofalakis

We introduce EigenRec; a versatile and efficient Latent-Factor framework for Top-N Recommendations that includes the well-known PureSVD algorithm as a special case.