Adversarial Explanations

Walt Woods joins us to discuss his paper [Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness](https://arxiv.org/abs/1906.02896) with co-authors Jack Chen and Christof Teuscher.

Guest

Walter Woods: Walt earned his Ph. D. from Portland State University for the conception and development of adversarial explanations, which leverage a security loophole in state-of-the-art neural networks to more robustly demonstrate their internal logic. He now works at Galois as a research engineer, melding machine learning with other formalisms on topics including grammar inference and malware generation.