Finding the largest linearly separable set of examples for a given Boolean function is a NP-hard problem, that is relevant to neural network learning algorithms and to several prob...
A new algorithm for on-line learning linear-threshold functions is proposed which efficiently combines second-order statistics about the data with the ”logarithmic behavior” ...
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...
Multiagent coordination algorithms provide unique insights into the challenging problem of alleviating traffic congestion. What is particularly interesting in this class of proble...
We present a trainable sequential-inference technique for processes with large state and observation spaces and relational structure. Our method assumes "reliable observation...