I've been reading a paper on Sparse PCA, which is:http://stats.stanford.edu/~imj/WEBLIST/AsYetUnpub/sparse.pdfAnd it states that, if you have $n$ data points, each represented with $p$ features, then, the complexity of PCA is $O(\min(p^3,n^3))$.Can someone please explain how/why?
How is the complexity of PCA $O(\min(p^3,n^3))$?
machine learning;time complexity;matrices