By the term "quantization", we refer to the process of using quantum mechanics in order to improve a classical algorithm, usually by making it go faster. In this paper, ...
We investigate under what conditions clustering by learning a mixture of spherical Gaussians is (a) computationally tractable; and (b) statistically possible. We show that using p...
Nathan Srebro, Gregory Shakhnarovich, Sam T. Rowei...
The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age chil...
This paper addresses challenges associated with the dynamics of knowledge in clusters and regional networks. It develops a conceptual framework, a methodology and a research agend...
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...