Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
Documents formatted in eXtensible Markup Language (XML) are becoming increasingly available in collections of various document types. In this paper, we present an approach for the...
Massih-Reza Amini, Anastasios Tombros, Nicolas Usu...
— This paper describes a panoramic view-based navigation in outdoor environments. We have been developing a two-phase navigation method. In the training phase, the robot acquires...
Hideo Morita, Michael Hild, Jun Miura, Yoshiaki Sh...
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Multiagent learning di ers from standard machine learning in that most existing learning methods assume that all knowledge is available locally in a single agent. In multiagent sy...