GeneRec is a generalization of the recirculation algorithm, and approximates Almeida–Pineda recurrent backpropagation.O'Reilly, R.C. Biologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm. Neural Computation, 8, 895–938. Abstract PDFGeneRec description in Computational explorations in cognitive neuroscience: understanding the mind by Randall C. O'Reilly, Yuko Munakata It is used as part of the Leabra algorithm for error-driven learning.
The symmetric, midpoint version of GeneRec is equivalent to the contrastive Hebbian learning algorithm (CHL).
See also Leabra O'Reilly (1996; Neural Computation)
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