Improved Techniques for Training GANs

Label smoothing, a technique from the 1980s recently independently re-discovered by Szegedy et. al [17], replaces the 0 and 1 targets for a classifier with smoothed values, like .9 or .1, and was recently shown to reduce the vulnerability of neural networks to adversarial examples [18].

[17] C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna. Rethinking the Inception Architecture for Computer Vision. ArXiv e-prints, December 2015. [18] David Warde-Farley and Ian Goodfellow. Adversarial perturbations of deep neural networks. In Tamir Hazan, George Papandreou, and Daniel Tarlow, editors, Perturbations, Optimization, and Statistics, chapter 11. 2016. Book in preparation for MIT Press.