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: 10.1.1.49.1968.
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