The deadline for meta-reviews is close (Dec 6th) and 1/3 reviewers hasn’t responded to our rebuttal yet. And others just updated their scores without any post-rebuttal comments 🙁

I understand that it is the job of AC to engage reviewers in active discussion, but I don’t see that happening.

We are releasing the new version of our MSG-GAN work. https://arxiv.org/abs/1903.06048 today.

Code at https://github.com/akanimax/msg-stylegan-tf.

We present much better experimental evaluation of the method and also incorporate the Multi-scale modifications in stylegan. We also experiment with our newly created (Indian Celebs) dataset (very small 3K) and get very nice results.

Please do check it out. Any feedback / suggestions are most welcome.

This paper. I’m not one of the authors or even familiar with the work but it certainly struck me by surprise reading the reviews.

I’m researching the uses and history of ML and I remember once running across a quote that I recall being from a famous ML researcher or practitioner. However I’m having no luck finding it.

It was something like, “So you want to use Machine Learning to solve your problem? Show me your data.”

Does anyone here have an idea which famous person in the ML community might have said something like this”?

Please check our new paper on searching robust architectures against adversarial attacks https://arxiv.org/abs/1911.10695.

TL;DR: We proposed a robust architecture search framework, which leverages one-shot NAS to understand the influence of network architectures against adversarial attacks. Our study revealed several valuable observations on designing robust network architectures.

https://towardsdatascience.com/how-to-actually-use-ml-in-production-text-classification-1e27bb5ac64d

A piece outlining an approach to deploying model servers for text classification models. fastText is used as an example, though the approach should work for models trained on all major frameworks.