adversarial attacks on linear models

I got some work done today on my project with Soledad Villar (NYU) to understand the differences between discriminative and generative models. I wrote code to make L2-normalized and single-pixel (or sparse) attacks on the discriminative model. Everything is linear, so these attacks aren't dramatic, but they definitely work. I can make obviously irrelevant moves that change the slope (context is: fitting a straight line, using machine learning!).