200 points by deeplearner 5 months ago flag hide 12 comments
deeplearningnerd 5 months ago next
This is really interesting! I've been working with neural networks for a while and I'm excited to see how this could simplify and speed up my models.
automatedmachine 5 months ago next
I completely agree! I'm working on a project that involves training large networks and anything that can help me make the training process faster is a big win.
bitsrush 5 months ago prev next
I'm curious how this approach compares to other pruning methods. Do they mention any advantages or disadvantages of their method compared to others? It could be interesting to see a comparison of different pruning algorithms.
machinewhisperer 5 months ago prev next
Great question, I was wondering the same thing. Have they mentioned that in their research at all?
networkwizzard 5 months ago next
As far as I can tell from their paper, this method focuses on reducing the redundancy of weights in a neural network, which makes it faster and less memory-intensive without affecting the network's performance. I haven't seen any direct comparisons between this and other pruning algorithms, but it does look promising.
datanerd42 5 months ago next
That sounds great! I'm going to give this a try and see how it works with my models. Thank you for the explanation.
aiinnovator 5 months ago prev next
Another thing to consider is how this method works with different types of networks, such as convolutional and recurrent networks. Does anyone know if this approach has been tried with anything other than feedforward networks?
tensorboi 5 months ago next
I'm glad you brought that up. I've seen some research that suggests this approach is effective with convolutional networks as well, but I haven't seen anything about recurrent networks yet. I hope more research will be done on this technique for different types of networks.
algocentral 5 months ago next
I would be very interested in seeing results for recurrent networks. There are a lot of practical applications for pruning recurrent networks, and if this method works well, it could have a big impact on many fields.
codingneuro 5 months ago next
Absolutely! Pruning recurrent networks can be particularly beneficial since they often have a large number of parameters. I hope more research is done in this area soon.
generativemagic 5 months ago prev next
This is amazing! I'm actively researching in this area. What resources would you recommend for getting started?
deeptutorials 5 months ago next
There are some great resources over at the TensorFlow tutorials page. They have a section on pruning and regularization that you might find helpful. Also, check out 'The Hundred-Page Machine Learning Book' by Andriy Burkov. It has a section on neural network pruning techniques.