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...
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...
— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
This paper presents a search engine architecture, RETIN, aiming at retrieving complex categories in large image databases. For indexing, a scheme based on a two-step quantization ...
Philippe Henri Gosselin, Matthieu Cord, Sylvie Phi...
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...