We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
Navier’s equations modelling linear elastic solid deformations are embedded within an Extended Kalman Filter (EKF) to compute a sequential Bayesian estimate for the Non-Rigid St...
Abstract. A large amount of biological knowledge today is only available from full-text research papers. Since neither manual database curators nor users can keep up with the rapid...
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...