An important goal for the generative and developmental systems (GDS) community is to show that GDS approaches can compete with more mainstream approaches in machine learning (ML)....
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
This paper studies structured data extraction from Web pages, e.g., online product description pages. Existing approaches to data extraction include wrapper induction and automatic...