Statistics Seminar Speaker: Andrew Gordon Wilson, 09/20/2017

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Wednesday Sep 20 2017

Statistics Seminar Speaker: Andrew Gordon Wilson, 09/20/2017

4:15pm @ G01 Biotechnology

The Statistics Seminar speaker for Wednesday, September 20, 2017, is Andrew Gordon Wilson, assistant professor of Operations Research and Information Engineering at Cornell University. Previously, Prof. Wilson was a research fellow in the Machine Learning Department at CMU with Eric Xing and Alex Smola. He completed his PhD in machine learning at the University of Cambridge. Andrew specializes in kernel methods, deep learning, and probabilistic modelling. His website is https://people.orie.cornell.edu/andrew.

Title: Bayesian Generative Adversarial Networks

Abstract: Through an adversarial game, the recently proposed generative adversarial networks (GANs) can implicitly learn rich distributions over images, audio, and data which are hard to model with an explicit likelihood.  In this talk, I will present a practical Bayesian formulation for unsupervised and semi-supervised learning with GANs.  Within this framework, we use stochastic gradient Hamiltonian Monte Carlo for marginalizing parameters.  The resulting approach can automatically discover complementary and interpretable generative hypotheses for collections of images.  Moreover, by exploring an expressive posterior over these hypotheses, we show that it is possible to achieve state-of-the-art quantitative results on major image classification benchmarks even with less than 1% of the labelled training data.   

The work will appear at NIPS 2017.

PDF iconA. Gordon Wilson - Flyer.pdf