We consider the problem of estimating CPU (distance computations) and I/O costs for processing range and k-nearest neighbors queries over metric spaces. Unlike the specific case ...
HMM-based acoustic models built from bootstrap are generally very large, especially when full covariance matrices are used for Gaussians. Therefore, clustering is needed to compac...
Abstract—The idea of an online visual vocabulary is proposed. In contrast to the accepted strategy of generating vocabularies offline, using the k-means clustering over all the ...
This paper illustrates the thesis research and process that led me to conceive, design and evaluate the Phototropic Memories device, a novel interface supporting the intimate shar...
Starting from an axiomatization of a generalization of Shannon entropy we introduce a set of axioms for a parametric family of distances over sets of partitions of finite sets. T...