Recently, several manifold learning algorithms have been proposed, such as ISOMAP (Tenenbaum et al., 2000), Locally Linear Embedding (Roweis & Saul, 2000), Laplacian Eigenmap ...
This paper employs general multivariate normal distribution to develop a new efficient statistical timing analysis methodology. The paper presents the theoretical framework of the...
Dimension reduction is a crucial step for pattern recognition and information retrieval tasks to overcome the curse of dimensionality. In this paper a novel unsupervised linear dim...
Yanwei Pang, Lei Zhang, Zhengkai Liu, Nenghai Yu, ...
Previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. Conventionally, principal component analy...
The properties of local image statistics are analyzed in a classic information theoretic setting. Local spatiochromatic image elements are projected into a space in which constitu...