[Lisa_seminaires] [TeaTalk] Karan Grewal, September 8, 13:45, AA6214

Dzmitry Bahdanau dimabgv at gmail.com
Lun 4 Sep 21:02:45 EDT 2017


Hi all,

Our next speaker is Karan Grewal, who is currently an intern at MILA. The
talk will take place at *AA6214, at 13:45, September 8*. Hope to see many
of you there!

*Title: *Variance Regularizing Adversarial Learning

*Abstract:* Generative Adversarial Networks have become a breakthrough
towards generating synthetic data in recent years, however many problems
may arise during training which result in the generator being unable to
learn the desired data distribution/manifold. Most notably, the
discriminator often overpowers the generator, which leads to a poor
training signal and vanishing gradients. We study the effects of the
discriminator's unnormalized output distribution on the generator's ability
to learn. To combat this problem, we propose Variance Regularizing
Adversarial Learning -- regularizing the discriminator's unnormalized
output distribution to fit a mixture of gaussians, yielding higher variance
and hence a lipschitz-like discriminator function. To do this, we provide
two methods: (1) using the KL-divergence as a penalty in the
discriminator's loss and (2) playing meta-adversarial games to force the
discriminator to fit a MoG. We show that our models are robust in the
presence of high training ratios and compare them to other variants of GANs.

*Bio:* Karan Grewal is an intern at MILA and a senior undergraduate student
at the University of Toronto. He is working on improving and stabilizing
generative models with Devon Hjelm and Yoshua Bengio. Previously, he worked
on applying machine learning to social contexts.

Dima
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