In this study Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF) and Nonnegative Tensor Factorization (NTF) are applied as dimension reduction methods in ...
Alexey Andriyashin, Jussi Parkkinen, Timo Jaaskela...
In this paper, we address the problem of hallucinating a high resolution face given a low resolution input face. The problem is approached through sparse coding. To exploit the fa...
We study a class of overrelaxed bound optimization algorithms, and their relationship to standard bound optimizers, such as ExpectationMaximization, Iterative Scaling, CCCP and No...
Non-negative Matrix Factorization (NMF, [5]) and Probabilistic Latent Semantic Analysis (PLSA, [4]) have been successfully applied to a number of text analysis tasks such as docum...
We give a bound on the expected reconstruction error for a general coding method where data in a Hilbert space are represented by finite dimensional coding vectors. The result can...