In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
A linear projective map called fuzzy discriminant projections has been proposed in this paper. Fuzzy discriminant projection (FDP) is motivated by locality preserving projections ...
— In this paper, we consider the issue of localization in anisotropic sensor networks. Anisotropic networks are differentiated from isotropic networks in that they possess proper...
The polyhedral model provides powerful abstractions to optimize loop nests with regular accesses. Affine transformations in this model capture a complex sequence of execution-reord...