Contrastive Hebbian learning
Contrastive Hebbian learning is a biologically plausible form of Hebbian learning. It has been shown to be equivalent in power to the backpropagation algorithms used in machine learning.[1]
It is based on the contrastive divergence algorithm, which has been used to train a variety of energy-based latent variable models.[2]
References
- ^ Xie, Xiaohui; Seung, H. Sebastian (2003-02). "Equivalence of backpropagation and contrastive Hebbian learning in a layered network". Neural Computation. 15 (2): 441–454. doi:10.1162/089976603762552988. ISSN 0899-7667. PMID 12590814.
{{cite journal}}: Check date values in:|date=(help) - ^ Qiu, Yixuan; Zhang, Lingsong; Wang, Xiao (2019-09-25). "Unbiased Contrastive Divergence Algorithm for Training Energy-Based Latent Variable Models".
{{cite journal}}: Cite journal requires|journal=(help), presented at the International Conference on Learning Representations, 2019
See also
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