This paper introduces XCSF extended with tile coding prediction: each classifier implements a tile coding approximator; the genetic algorithm is used to adapt both classifier cond...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Abstract. We present the first (to our knowledge) approximation algorithm for tensor clustering—a powerful generalization to basic 1D clustering. Tensors are increasingly common...
Background: Structural genomics initiatives are producing increasing numbers of threedimensional (3D) structures for which there is little functional information. Structure-based ...
Sungroh Yoon, Jessica C. Ebert, Eui-Young Chung, G...
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...