Before revision:  We present a two stage neural optimization approach as an alternative to conventional and randomized SVD techniques , where the  memory requirement depends explicitly on the feature dimension and desired rank, independent of the sample size.
After revision:  We present a two stage neural optimization approach as an alternative to randomized SVD that satisfies the tail-energy lower bound given by Eckart-Young-Mirsky (EYM) theorem. Range-Net is a deterministic two-stage neural optimization approach with random initialization , where the memory requirement depends explicitly on the feature dimension and desired rank, independent of the sample size.