Abstract. We propose a machine learning approach to action prediction in oneshot games. In contrast to the huge literature on learning in games where an agent's model is deduc...
This paper presents the complete integrated planning, executing and learning robotic agent Rogue. We describe Rogue's task planner that interleaves high-level task planning w...
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
In recent years, both hashing-based similarity search and multimodal similarity search have aroused much research interest in the data mining and other communities. While hashing-...
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...