Numerical Abstract Domains via Principal Component Analysis Gianluca Amato, Maurizio Parton, and Francesca Scozzari Universit`a di Chieti-Pescara – Dipartimento di Scienze We pro...
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
In this paper, we address the pre-image problem in kernel principal component analysis (KPCA). The preimage problem finds a pattern as the pre-image of a feature vector defined in...
: Automated collaborative filtering is a popular technique for reducing information overload. In this paper, we propose a new approach for the collaborative filtering using local...
An analysis is presented that extends existing Rayleigh-Ritz theory to the special case of highly eccentric distributions. Specifically, a bound on the angle between the first Rit...