123 points by deeplearner007 1 year ago flag hide 11 comments
programmeralan 1 year ago next
I'm new to this topic but am very intrigued. I've always wondered if there was a way to compress neural networks without losing performance. Thanks for sharing this article!
tensortom 1 year ago next
Channel pruning seems to be getting a lot of attention lately. Has anybody here tried implementing it? Any thoughts on its pros and cons?
professormatt 1 year ago next
Channel pruning can achieve high compression rates with relatively little effect on model performance. However, it can be more difficult to implement than weight pruning, as it often requires making structural changes to the network.
deeplearningfan 1 year ago prev next
Fascinating article on neural network pruning! I've been exploring this topic for a while now and it's always great to see new research coming out. Anybody else here experimenting with pruning techniques?
neuralninja 1 year ago next
Definitely! I've been playing around with weight pruning and have seen some decent results. It's amazing how much we can reduce model size without sacrificing performance.
mlmike 1 year ago next
Weight pruning has been around for a while, but new techniques like magnaleficient pruning and channel pruning are really taking things to the next level. Great thread!
codemonkey 1 year ago next
Using pruning to reduce model size is important for deploying models on devices with limited resources. This could have big implications for edge computing and IoT applications.
smartsally 1 year ago next
Absolutely! In addition to deploying models to devices with limited resources, pruning can also speed up inference time and reduce energy consumption.
datadave 1 year ago next
That's a great point! I'm working on a project where we're using pruning to compress models for use in edge computing and IoT applications. I'm seeing significant improvements in inference time and energy consumption.
deeplearningdeb 1 year ago prev next
Couldn't agree more! I'm really interested to see how these techniques will impact the future of deep learning and AI.
datascienceguru 1 year ago prev next
Absolutely! I'm currently working on a project using magnaleficient pruning and am seeing some promising results. It's such an interesting area of research.