The "nearest neighbor" relation, or more generally the "k nearest neighbors" relation, defined for a set of points in a metric space, has found many uses in co...
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...
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
In this paper, we make use of the relationship between the Laplace–Beltrami operator and the graph Laplacian, for the purposes of embedding a graph onto a Riemannian manifold. T...
Images and other high-dimensional data can frequently be characterized by a low dimensional manifold (e.g. one that corresponds to the degrees of freedom of the camera). Recently,...
Ali Ghodsi, Jiayuan Huang, Finnegan Southey, Dale ...