We explore a general Bayesian active learning setting, in which the learner can ask arbitrary yes/no questions. We derive upper and lower bounds on the expected number of queries r...
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
We present several new algorithms for multiagent reinforcement learning. A common feature of these algorithms is a parameterized, structured representation of a policy or value fu...
Carlos Guestrin, Michail G. Lagoudakis, Ronald Par...
In this paper we present a novel two-stage method to realize a lightweight but very capable hardware implementation of a Learning Classifier System for on-chip learning. Learning C...
Andreas Bernauer, Johannes Zeppenfeld, Oliver Brin...
An important class of image data sets depict an object undergoing deformation. When there are only a few underlying causes of the deformation, these images have a natural lowdimen...