A fast-growing body of research in the AI and machine learning communities addresses learning in games, where there are multiple learners with different interests. This research a...
Kernel learning plays an important role in many machine learning tasks. However, algorithms for learning a kernel matrix often scale poorly, with running times that are cubic in t...
Concept Maps constitute one of the tools mostly used in learning management due to the possibility that they offer to contextualize learning, share knowledge and for learning to le...
Leonel Iriarte Navarro, Manuel Marco Such, Daniel ...
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Coordinate gradient learning is motivated by the problem of variable selection and determining variable covariation. In this paper we propose a novel unifying framework for coordi...