I was wondering if there are other popular alternatives to back-propagation through which neural networks can learn the weights.
.
many pointers can be found here :
http://www.breloff.com/no-backprop/
http://www.breloff.com/no-backprop-part2/
and there always is the good old Hebb rule
https://www.ece.ucsb.edu/wcsl/people/aseem/Aseem_stuff/hebbian_preprint.pdf
Article Deep Learning With Asymmetric Connections and Hebbian Update...
also regarding BP through time
Preprint Biologically inspired alternatives to backpropagation throug...
now; i would not say these are "poipular" alternatives ... but these are definitely alternatives to BP learning.
these are some alternatives to BP learning.
The Alternative to backpropagation through which a neural network can learn is the Elman neural network and Jordan neural network.
also there is many of learning rule to training neural network for example Hebbian learning , etc.
the attached file is contain many of learning rule.
Good luck
Titas De-
Thank you for your excellent question. You may use genetic algorithm or other approaches- see the link below for abstracts-
https://www.sciencedirect.com/topics/engineering/genetic-algorithm
Thank you Fabrice Clerot , Adnan Riaz , Shahbaa I. Khaleel and Samy Azer
You may also check this paper from Google on approximate backprop
https://arxiv.org/abs/2001.06232
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