Towards Semi-supervised Manifold Learning: UKR with Structural Hints

Authors:
Jan Steffen;Stefan Klanke;Sethu Vijayakumar;Helge Ritter
Affiliations:
Neuroinformatics Group, Bielefeld University, Germany;Institute of Perception, Action and Behaviour, University of Edinburgh, UK;Institute of Perception, Action and Behaviour, University of Edinburgh, UK;Neuroinformatics Group, Bielefeld University, Germany
Venue:
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Year:
2009

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Abstract

We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-supervised way. These new extensions are targeted at representing a dextrous manipulation task. We thus evaluate the effectiveness of the proposed mechanisms on appropriate toy data that mimic the characteristics of the aimed manipulation task and thereby provide means for a systematic evaluation.