GeneRec

GeneRec is a generalization of the recirculation algorithm, and approximates Almeida-Pineda recurrent backpropagation.[1][2] It is used as part of the Leabra algorithm for error-driven learning.[3]

The symmetric, midpoint version of GeneRec is equivalent to the contrastive Hebbian learning algorithm (CHL).[1]

## See also

[edit]

* Leabra
* O'Reilly (1996; Neural Computation)

## References

[edit]

1. ^ a b O'Reilly, R.C. Biologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm. Neural Computation, 8, 895–938. Abstract PDF
2. ^ GeneRec description in Computational explorations in cognitive neuroscience: understanding the mind by Randall C. O'Reilly, Yuko Munakata
3. ^ Leabra overview in Emergent

This neuroscience article is a stub. You can help Wikipedia by expanding it.

|

* v
* t
* e

This machine learning-related article is a stub. You can help Wikipedia by expanding it.

|

* v
* t
* e

*[v]: View this template
*[t]: Discuss this template
*[e]: Edit this template