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[D] Is it possible for us to make fixed-size multilayer perceptrons (MLP's) provably converge?
4 projects | /r/MachineLearning | 12 Mar 2022

But what happens when you increase the number of layers? I verified that the gradient calculation is correct using Jax now, before I had the sum-squared-error gradient instead of the mean, so I just changed it to the mean (see commit history). I don't see convergence for most configurations with more than one layer.

1 project | /r/u_tchlux | 12 Mar 2022

Get the code for these experiments here.
[D] MLP's are actually nonlinear ➞ linear preconditioners (with visuals!)
5 projects | /r/MachineLearning | 24 Oct 2021

A great exercise! No better way to test your knowledge either. I haven't implemented a SVM, because quadratic programming is still difficult for me to comprehend. Would love to one day though! Not sure if you saw, but all of this work in this post was done with my own Fortran implementation of a neural network (I'm using it for my personal research).
A note from our sponsor - SaaSHub
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