It was a love at first sight. The Singular Value Decomposition-SVD came into my (research) life back in 2002 as a crucial step of a whole family of Multivariate Data Analysis methods, such as Correspondence Analysis, Principal Component Analysis, Multidimensional Scaling and other. Most of us take advantage of its nice geometric properties as a “black box”, since it’s an important factorization technique with a wide spectrum of applications in statistics and machine learning.

I was wondering how many research articles mention the term SVD in a time period from 1970 to 2008, so I did a series of searches in Google Scholar. SVD gains more and more attention (see Figure below), especially after 1990, with a boom during the 00s. However, I can’t explain the fall in 2008 (I bet it’s not statistically significant :p). How long can the SVD stand the competition of more efficient methods? Will see.

SVD Search Results in Google Scholar

[read more at Wikipedia]

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