250 points by deeplearner 7 months ago flag hide 12 comments
deeplearningfan123 7 months ago next
Fascinating work! I've been exploring the world of pruning and it's incredible to see how much fat can be trimmed off our neural networks without affecting their performance. I'd love to know more about the techniques and tools you used for this study. :)
airesearcher347 7 months ago next
Hey @DeepLearningFan123, I agree! I found the iterative pruning approach to be very effective in preventing accuracy loss after reducing the complexity of the model. We used TensorFlow's built-in pruning functions to make it easier, but I think there's still room for improvement to further optimize the pruning process.
tensorflowfan678 7 months ago next
I'm curious, did you try any third-party pruning libraries, such as Nervana's or BrainEff's? I've heard good things about their performance, but I have yet to test them out myself. #TensorFlow #AI #DeepLearning
deltanetworkuser9 7 months ago next
@TensorFlowFan678 Thanks for the suggestion. Although we have had some success using the built-in TensorFlow tools, I'm interested in checking out these libraries. Our team will definitely take this into account. :)
mltutorialsguru45 7 months ago next
Another technique I've seen being used successfully is Magnitude-based Pruning. By selecting the smallest weights for pruning, we retain the most relevant connections in our neural networks. #HackerNews #MachineLearning #DeepLearning
deeplearningfan123 7 months ago next
@MLTutorialsGuru45 That's an interesting point, and it's actually something we've tried in our approach as well. We found that the iterative method combined with magnitude pruning yielded the best results. Thanks for sharing!
pytorchstan686 7 months ago prev next
While I think the results are impressive, I feel the need to point out that moving from custom pruning methods to a more generalized, automated approach might be beneficial. I find this to be true especially when working with complex models. #AI #DeepLearning #Pytorch #HackerNews
automatepruning321 7 months ago next
@PytorchStan686 Absolutely! Automated pruning techniques, like the Lottery Ticket Hypothesis and AutoML, can help with generalizability and ease of use. I would recommend checking out applica... Oops, seems I hit the character limit. In short, be sure to check out AutoML!
pytorchstan686 7 months ago next
@AutomatePruning321 I have heard of the Lottery Ticket Hypothesis, but I haven't yet given AutoML a try. I'll definitely look into that. Thanks for the tip! #AI #DeepLearning #Pytorch #HackerNews
accuracyadvocate12 7 months ago prev next
Though it's great to reduce the network's complexity and computational resources, I'd also like to remind everyone to be cautious about performance degradation. A more accurate model may be more resource-intensive but can be well worth it. #AI #HackerNews #DeepLearning
efficienttrainer789 7 months ago next
@AccuracyAdvocate12 I completely agree that accuracy and performance are important considerations. However, with pruning, you can reduce complexity and computational resources without significant performance loss, especially when using techniques like the ones mentioned in this study. Still, it's important to find the ideal balance. #AI #DeepLearning #HackerNews
aijustice456 7 months ago next
Sure, balance is key, but I think this depth of pruning opens the door for some exciting possibilities. We should keep investigating techniques to reduce neural network complexity without sacrificing performance. #AI #DeepLearning #HackerNews