Backpropagation through structure

Backpropagation Through Structure (BPTS) is a gradient-based technique for training recursive neural nets (a superset of recurrent neural nets) and is extensively described in a 1996 paper written by Christoph Goller and Andreas Küchler.[1]

References

  1. ↑ Kuchler, Andreas. "Learning Task-Dependent Distributed Representations by Backpropagation Through Structure". psu.edu. CiteSeerX 10.1.1.49.1968Freely accessible.
This article is issued from Wikipedia - version of the 11/10/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.