Abstract
In this paper, we propose a new interpretation of the information maximization method (InfoMax) from a perspective of the rate distortion theory. We show that under specific conditions, InfoMax is equivalent to the minimization of a compression rate under the constraint of zero distortion. Zero distortion, or equivalently, zero reconstruction error between the input and its reconstruction, does not provide meaningful solutions in many cases. Based on the new interpretation, we extend InfoMax to be able to deal with non-zero distortion and also to learn under/over-complete representations. Experimental results on synthetic as well as real data show the effectiveness of our method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.