Reinforcement Learning Reward Functions for Unsupervised Learning

Authors:
Colin Fyfe;Pei Ling Lai
Affiliations:
Southern Taiwan Institute of Technology, Tainan, Taiwan;Southern Taiwan Institute of Technology, Tainan, Taiwan
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

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Abstract

We extend a reinforcement learning algorithm, REINFORCE [13] which has previously been used to cluster data [10]. By using base Gaussian learners, we extend the method so that it can perform a variety of unsupervised learning tasks such as principal component analysis, exploratory projection pursuit and canonical correlation analysis.