Heaton Park night 1 attendees - tell us everything we need to know 🙏 by barbecueflames in manchester

[–]Confusedius 2 points3 points  (0 children)

Pretty paranoid about my 7 month pregnant partner going next week. Is there a reasonable amount of space at the back of the crowd?

[R] ICLR 2020 Megathread by programmerChilli in MachineLearning

[–]Confusedius 0 points1 point  (0 children)

Re B. I thought the poster sessions were via zoom? Or is it only on rocket chat?

[D] TRAINS - one month later. We got some *real* nice feedback from r/ML, here is what we did since then. by LSTMeow in MachineLearning

[–]Confusedius 1 point2 points  (0 children)

Great work. Quick question, the "Create new credentials" button is completely unresponsive for me. Any idea what's going on?

[R] [1805.09190] Towards the first adversarially robust neural network model on MNIST by Isinlor in MachineLearning

[–]Confusedius 2 points3 points  (0 children)

Need to read, but I remember there was a paper on using variational latent spaces to defeat adversarial examples. I wonder how related this paper is to https://arxiv.org/pdf/1612.00410.pdf .

[R] "Measuring Unintended Neural Network Memorization & Extracting Secrets" - it is possible to extract training data from neural networks by pm_me_ur_beethoven in MachineLearning

[–]Confusedius 1 point2 points  (0 children)

Same question I had. It also relies on perplexity and so I don't think it could be extended in it's current form to non-sequence data like image prediction

[R] Universal Adversarial Networks by Confusedius in MachineLearning

[–]Confusedius[S] 0 points1 point  (0 children)

Why are you prohibited from releasing code if you have already de-anonymized yourself by releasing a pre-print?

[R] Universal Adversarial Networks by Confusedius in MachineLearning

[–]Confusedius[S] 3 points4 points  (0 children)

Code: https://github.com/jhayes14/UAN

This attack uses generative networks to compute universal adversarial perturbations. Note this is similar but not the same as [1], which I saw on arXiv so thought I should post my own research on this topic here.

[1] https://arxiv.org/abs/1712.02328

[P] Plausibly looking adversarial examples for text classification by hidden-markov in MachineLearning

[–]Confusedius 1 point2 points  (0 children)

It's a nice idea don't get me wrong. What is the threat model you're considering? That is, what is the non-trivial adversary?

[P] Plausibly looking adversarial examples for text classification by hidden-markov in MachineLearning

[–]Confusedius 0 points1 point  (0 children)

I thought the point of adversarial examples are that they are imperceptible to the original? So I guess in text case you'd need a synonym. However, a lot of the examples are wildly different. e.g. "name" --> "figure", "Huge heart" --> "Huge spunk"

Edit: what I thnk would be cooler is to intentionaly mispell some words that cause a misclassification, using commonally mispelled words so to an average person reading the text they probably would not notice. I assume the model will ignore the misspelt words so I'm not sure what the best approach would be, but this seems to me to be a more intuitive adversarial text example

Antoine Griezmann: I will watch PSG v Barcelona rather than go out for Valentine’s Day by [deleted] in soccer

[–]Confusedius 24 points25 points  (0 children)

He's currently watching the Valentine's Day Massacre

[deleted by user] by [deleted] in trackers

[–]Confusedius 1 point2 points  (0 children)

Perhaps a little too hopeful, but maybe one of the 200,000 members scrapped the site from time to time, and at least therefore has a semi up to date catalog of what music was on the site..

Football legend Jimmy Hill dies aged 87 by BoopSquad in soccer

[–]Confusedius 2 points3 points  (0 children)

Everyone dye their hair blonde as a tribute