123 points by deeplearner 1 year ago flag hide 10 comments
deeplearner 1 year ago next
Fantastic article! I've been experimenting with neural network obfuscation techniques and this guide really dives deep into the intricacies. The comparison between gradient masking and pruning has proven insightful.
networkweaver 1 year ago next
I've been applying some of the obfuscation techniques mentioned in your guide, and the results have been quite interesting. I found distillation to affect performance only slightly while making the model considerably more obscure. Keep up the great work!
aiguru 1 year ago prev next
The different adversarial attack strategies mentioned were enlightening. I liked how the guide discussed multiple ways of obscuring the gradients in the network. I've been curious about this topic lately and this has definitely given me a lot to think about.
datascienceenthusiast 1 year ago next
I'm relatively new to the field and the article's clear explanations have been very helpful. Understanding the trade-off betweenNN transparency and obfuscation was the main challenge I've encountered so far, and the examples provided certainly eased my learning process.
codealchemist 1 year ago prev next
Additionally, the section about differential privacy was very interesting. It offered a perspective I hadn't considered in the context of neural network obfuscation. I can see the effectiveness of the techniques used to obscure sensitive information. Appreciate it!
aiadvocate 1 year ago next
The adoption of differential privacy has been on the rise, and it's undoubtedly essential for models that deal with sensitive information. You summed it up pretty well here. Good job!
tensortitan 1 year ago prev next
I'm impressed by the exhaustive coverage of the topic. The inclusion of deep learning frameworks' in-built obfuscation methods is a great bonus for practitioners. I cannot wait to try these methods out in my upcoming projects.
innovativealgo 1 year ago next
Frameworks with built-in obfuscation tools surely simplify the work for developers, thanks for emphasizing this point. I'd be interested in hearing more about your experiments in upcoming publications.
optimizationwarrior 1 year ago prev next
Great to see such an elaborate guide on obscuring neural networks. The integration of quantization and pruning for embedding safety struck a chord. Can't wait to experiment more with these newly learned concepts.
quantizationking 1 year ago next
@OptimizationWarrior It's interesting to see how quantization complements pruning for embedding safety. I've also noticed an improvement in my work when combining these techniques. Keep up the great discussion!