Adversarially Robust Deep Learning

Speaker: Prof. Zico Kolter
Affiliation: Carnegie Mellon University

Abstract: Deep learning is often seen as the “breakthrough” AI technology of recent years, revolutionizing areas spanning computer vision, natural language processing, and game playing. However, if we seek to deploy such systems in real-world, safety-critical domains, a starker reality emerges: deep learning systems are notoriously brittle, sensitive to so-called adversarial attacks, where an adversary manipulates inputs to the algorithm to vastly degrade its performance (both at training time or test time). In this talk, I will present recent progress in developing new deep learning systems that are _provably_ robust against such attacks. Specifically, I will present two paradigms for building robust deep learning architectures: convex relaxations and randomized smoothing. I will discuss how these approaches can be used to build classifiers that are robust against test-time data manipulation and highlight recent work on using similar techniques to build classifiers that are provably secure against training-time attacks (also known as data poisoning attacks). I will end with some discussion on the challenges that remain in robust deep learning, and the potential directions forward.

Biography: Zico Kolter is an Associate Professor in the Computer Science Department at Carnegie Mellon University, and also serves as chief scientist of AI research for the Bosch Center for Artificial Intelligence. His work focuses on the intersection of machine learning and optimization, with a large focus on developing more robust, interpretable, and rigorous methods in deep learning. In addition, he has worked in a number of application areas, highlighted by work on sustainability and smart energy systems. He is a recipient of the DARPA Young Faculty Award, and best paper awards at ICML (honorable mention), KDD, PESGM, and IJCAI.

For more information, contact Prof. Suhas Diggavi (suhas@ee.ucla.edu)

Date/Time:
Date(s) - Sep 30, 2019
12:30 pm - 1:30 pm

Location:
EE-IV Shannon Room #54-134
420 Westwood Plaza - 5th Flr., Los Angeles CA 90095