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In this paper, we combine feedback alignment learning method with popular optimization techniques such as RMSprop and Adam, and investigate its effect on the ...
Abstract—The error backpropagation algorithm is a representative learning method that has been used in most deep network models.
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Bibliographic details on Effect of Optimization Techniques on Feedback Alignment Learning of Neural Networks.
In this work, the feedback alignment principle is used for training hidden layers more independently from the rest of the network, and from a zero initial ...
This work demonstrates that meta-learning procedures can optimize neural networks that learn online using feedback connections and local plasticity rules. These ...
Here, we present physical deep learning by extending a biologically inspired training algorithm called direct feedback alignment. Unlike the original algorithm, ...
The effect of choosing optimizer algorithms to improve computer ...
www.ncbi.nlm.nih.gov › PMC9514986
Sep 28, 2022 · Optimization algorithms are used to improve model accuracy. The optimization process undergoes multiple cycles until convergence.
Jun 11, 2019 · In this work, we focus on direct feedback alignment and present a set of best practices justified by observations of the alignment angles. We ...
Missing: Optimization Techniques
6 days ago · Feedback Alignment (FA) methods are biologically inspired local learning rules for training neural networks with reduced communication ...
We first show that learning in shallow networks pro- ceeds in two steps: an alignment phase, where the model adapts its weights to align the approximate.
Missing: Techniques | Show results with:Techniques