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" (PDF). psu.edu. CiteSeerX 10.1.1.49.1968 Freely accessible.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.