Seminars

Distinguished Seminar in Optimization & Data (DSOD)

I am a co-organizer of the Distinguished Seminar in Optimization & Data (DSOD), an interdepartmental talks series at the University of Washington, focused on all aspects of optimization and data science. The speakers of 2023 (see website for details):
Date Speaker Title
1/9/23 √Čva Tardos, Cornell University Stability and Learning in Strategic Queueing Systems
4/3/23 Damek Davis, Cornell University Leveraging "partial" smoothness for faster convergence in nonsmooth optimization
5/1/23 Misha Belkin, University of California, San Diego The Challenges of Training Infinitely Large Neural Networks
5/22/23 Philippe Rigollet, MIT Statistical applications of Wasserstein gradient flows
6/5/23 Ting-Kei Pong, Hong Kong Polytechnic University The Challenges of Training Infinitely Large Neural Networks


Machine learning and optimization seminar (ML-OPT)

The machine learning and optimization seminar is a venue for internal and external speakers to present their work on machine learning and data science. It takes place every Friday at 1:30 pm and is primarily intended for graduate students and post-docs to publicize their work. Join the mailing list here. This seminar is supported by the Institute for the Foundations of Data Science (IFDS), an NSF program I am a co-PI of. Please drop me an email if you think you may want to speak at this seminar.