Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some application...
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
We describe a system that successfully transfers value function knowledge across multiple subdomains of realtime strategy games in the context of multiagent reinforcement learning....
For many ranking applications we would like to understand not only which items are top-ranked, but also why they are top-ranked. However, many of the best ranking algorithms (e.g....
Ansaf Salleb-Aouissi, Bert C. Huang, David L. Walt...
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...