A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Abstract. This paper presents an innovative, adaptive variant of Kohonen’s selforganizing maps called ASOM, which is an unsupervised clustering method that adaptively decides on ...
We propose a new theoretical framework for generalizing the traditional notion of covariance. First, we discuss the role of pairwise cross-cumulants by introducing a cluster expan...
We describe and evaluate experimentally a method for clustering words according to their distribution in particular syntactic contexts. Words are represented by the relative frequ...
Fernando C. N. Pereira, Naftali Tishby, Lillian Le...
—We introduce a novel metric space search data structure called EGNAT, which is fully dynamic and designed for secondary memory. The EGNAT is based on Brin’s GNAT static index,...