We investigate the problem of evaluating the performance of text processing algorithms on inputs that contain errors as a result of optical character recognition. A new hierarchic...
We present spatio-temporal feature descriptors that can be inferred from video and used as building blocks in action recognition systems. They capture the evolution of ``elementar...
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
This paper provides a general mechanism and a solid theoretical basis for performing planning within Belief-Desire-Intention (BDI) agents. BDI agent systems have emerged as one of...
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...