Technical - Partner Event
AI Seminar – Kamalika Chaudhuri
When
March 12, 2021 - March 12, 2021
12:00 PM – 1:00 PM MST
Where
Online
Online
Abstract: The vast majority of computer science literature in privacy can be broadly divided into two categories -- differential, where the idea is to ensure that participation of an entity or an individual does not change the outcome significantly and inferential, where we are trying to bound the inferences an adversary can make based on auxiliary information.
In this talk, I will present two new case-studies, one in each framework. The first looks at a form of inferential privacy that allows more fine-grained control in a local setting than the individual level. The second looks at privacy against adversaries who have bounded learning capacity, and has ties to the theory of generative adversarial networks.
Joint work with Joseph Geumlek, Jacob Imola and Ashwin Macchanavajhhala
Presenter Bio: Kamalika Chaudhuri received a Bachelor of Technology degree in Computer Science and Engineering in 2002 from Indian Institute of Technology, Kanpur, and a PhD in Computer Science from University of California at Berkeley in 2007. After a postdoc at the Information Theory and Applications Center at UC San Diego, she joined the CSE department at UC San Diego as an assistant professor. She received an NSF CAREER Award in 2013 and a Hellman Faculty Fellowship in 2012.
Kamalika's research interests are in the foundations of trustworthy machine learning, which includes problems such as learning from sensitive data while preserving privacy, learning under sampling bias, and in the presence of an adversary. She is particularly interested in privacy-preserving machine learning, which addresses how to learn good models and predictors from sensitive data, while preserving the privacy of individuals.
The University of Alberta Artificial Intelligence (AI) Seminar is a weekly meeting where researchers (including students, developers, and professors) interested in AI can share their current research. Presenters include local speakers from the University of Alberta and industry as well as other institutions. The seminars discuss a wide range of topics related in any way to Artificial Intelligence, from foundational theoretical work to innovative applications of AI techniques to new fields and problems are of interest. Learn more at the AI Seminar website and by subscribing to the mailing list!
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