Closed-Loop Deep Learning with Robotics, NECO Vol 32, No 11
Dear Colleagues, In our paper we present Closed-Loop Deep Learning which combines the power of deep learning and classical control to create an efficient analogue multi-layered fast learning paradigm, for robotic navigation. At the heart of this algorithm is an error signal that arises from a reflex which is delicately used to both drive the closed loop system and train the deep learner simultaneously. Through mathematical derivation in z-space we show how to implement back-propagation in a closed-loop system. Preprint: https://arxiv.org/abs/2001.02970 Neural Computation (final version): https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01317?journalCode=ne... Please do not hesitate to get in touch for a copy of the paper and to discuss your thoughts. Warmest Regards, Sama Daryanavard Dr Bernd Porr Biomedical Engineering Division, School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.
participants (1)
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Sama Daryanavard (PGR)