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):
|1/9/23||Éva 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.