PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Towards Semi-supervised Manifold Learning: UKR with Structural Hints
Jan Steffen, Stefan Klanke, Sethu Vijayakumar and Helge Ritter
In: WSOM 2009, Orlando, Florida, USA(2009).


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.

PDF - PASCAL Members only - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5899
Deposited By:Stefan Klanke
Deposited On:08 March 2010