We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
In this document, we describe a light-weighted ontology mediation method that allows users to send semantic queries to distant data repositories to browse for learning object meta...
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...
Reinaldo A. C. Bianchi, Raquel Ros, Ramon Ló...
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
Typographic and visual information is an integral part of textual documents. Most information extraction systems ignore most of this visual information, processing the text as a l...