We present a near linear time algorithm for constructing hierarchical nets in finite metric spaces with constant doubling dimension. This data-structure is then applied to obtain...
We propose a novel algorithm for clustering data sampled from multiple submanifolds of a Riemannian manifold. First, we learn a representation of the data using generalizations of...
Abstract. Distribution of object colors has been used in computer vision for recognition and indexing. Most of the recent approaches to this problem have been focused on de ning op...
The linear discriminant analysis (LDA) technique is very popular in pattern recognition for dimensionality reduction. It is a supervised learning technique that finds a linear tran...
In the paper the idea is presented that emotions are the result of a high dimensional optimization process happening in the unconscious mapped onto the low dimensional conscious. I...