This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Multiagent Reinforcement Learning algorithms, combining Case-Based Reasoning...
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...
We introduce a technique to visualize the gradual evolutionary change of the shapes of living things as a morph between known three-dimensional shapes. Given geometric computer mo...
David F. Wiley, Nina Amenta, Dan A. Alcantara, Deb...
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...