We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
We present lower bounds on the space required to estimate the quantiles of a stream of numerical values. Quantile estimation is perhaps the most studied problem in the data stream ...
Abstract. This article describes an algorithm for pose or motion estimation based on clustering of parameters in the six-dimensional pose space. The parameter samples are computed ...
Abstract-- Simple and efficient computational algorithms for nonparametric wavelet-based identification of nonlinearities in Hammerstein systems driven by random signals are propos...
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...