Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
We describe a new approach for elucidating the nonlinear degrees of freedom in a distribution of shapes depicted in digital images. By combining a deformation-based method for mea...
Gustavo K. Rohde, Wei Wang, Tao Peng, Robert F. Mu...
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Abstract— Nonlinear mapping is an approach of multidimensional scaling where a high-dimensional space is transformed into a lower-dimensional space such that the topological char...
Auralia I. Edwards, Andries Petrus Engelbrecht, Ne...
Many semi-supervised learning algorithms only
deal with binary classification. Their extension to the
multi-class problem is usually obtained by repeatedly
solving a set of bina...