This paper compares three similar loop-grouping methods. All methods are based on projecting the n-dimensional iteration space Jn onto a k-dimensional one, called the projected sp...
Ioannis Drositis, Georgios I. Goumas, Nectarios Ko...
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data poin...
Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality Preserving Projections (LPP). These are linear projecti...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
A linear projective map called fuzzy discriminant projections has been proposed in this paper. Fuzzy discriminant projection (FDP) is motivated by locality preserving projections ...