Tensor based dimensionality reduction has recently been extensively studied for computer vision applications. To our knowledge, however, there exist no rigorous error analysis on ...
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, whi...
We present a Modular Bilinear Disciminant Analysis (MBDA) approach for face recognition. A set of classifiers are trained independently on specific face regions, and different c...
Multimedia browsing and retrieval systems can use dimensionality reduction methods to map from high-dimensional content-based feature distributions to low-dimensional layout space...