123 points by nnresearcher 6 months ago flag hide 27 comments
john_doe 6 months ago next
Fascinating! This could be a game-changer for the field of deep learning.
ai_enthusiast 6 months ago next
Absolutely, I'm particularly curious about the impact on model size and inference time.
machine_learning_for_fun 6 months ago prev next
I'm going to try this on my own projects. Thanks for sharing!
data_analysis 6 months ago prev next
How does this compare to other existing pruning techniques?
neuralnet_hacker 6 months ago prev next
Excellent work! I'm excited to see the next steps with this research.
coder_mb 6 months ago prev next
I'm curious about how many iterations it takes for pruning to work well.
fenty_, 6 months ago prev next
Definitely brings great potential for real-world applications.
software_craftsman 6 months ago prev next
Thanks for sharing! I'm looking forward to applying this in practice.
young_researcher 6 months ago prev next
What could be the implications on accuracy?
proven_researcher 6 months ago prev next
The results do seem promising. I'll wait for further research to fully understand the impact.
early_adopter 6 months ago next
Generally agree! But I think it's worth experimenting with new methods like these.
tech_savvy 6 months ago prev next
Could this be integrated with existing DL frameworks easily?
professor 6 months ago next
It would require changes to the backend. But certainly a possible path for further development.
passionate_learner 6 months ago prev next
How does it choose which connections to prune?
algorithm_innovator 6 months ago next
Typically it's based on network weights and other metrics.
deep_learning_beginner 6 months ago prev next
I'm also curious about the implementation details.
hackerptr 6 months ago prev next
What's the largest model size reduced?
experimental_engineer 6 months ago next
I believe they've reduced models by up to 70% in some cases.
data_scientist_guy 6 months ago prev next
Impressive! I wonder how this would apply to huge models.
future_ai_tech 6 months ago prev next
Implementing this in popular libraries like TensorFlow and Pytorch would be awesome.
clever_user 6 months ago prev next
Does the pruning impact the receptive field of the neural network?
new_neuralnet_dev 6 months ago next
That's an interesting point. Typically, it might introduce some constraints to it.
quantum_computing_champ 6 months ago prev next
I'm looking forward to seeing parallelizations for these pruning strategies.
nonlinear_thinking 6 months ago prev next
Could we extend this method to other architectures?
thoughtful_theorist 6 months ago next
Absolutely! It'd be interesting to explore this in other types of networks.
senior_scientist 6 months ago prev next
Typically, there are trade-offs between accuracy and compression rate.
academic_mentor 6 months ago next
Right, it also depends on the measure of accuracy used by the researchers.