Distinguished Seminar in Optimization & Data
Distinguished Seminar in Optimization & Data
The Distinguished Seminar in Optimization & Data is an interdepartmental talks series at the University of Washington, focused on all aspects of optimization and data science. It is a new incarnation of the CORE seminar that ran from 2013-2020.
The series is funded by the Institute for the Foundations of Data Science , the Pacific Institute of Mathematical Sciences (PIMS), and the home departments of the organizers.
Past Events
- An Automatic Finite-Sample Robustness Check: Can Dropping a Little Data Change Conclusions? (Tamara Broderick, MIT) -
- Average-case optimization: search vs. decision (Tselil Schramm, Stanford) -
- Weak to Strong Generalization in Random Feature Models (Nathan (Nati) Srebro, Toyota Technological Institute at Chicago and University of Chicago) -
- Mistake, Manipulation, and Margin Guarantees in Online Strategic Classification (Fatma Kilinc-Karzan) -
- High-throughput optimization of DNA-aptamer secondary structure for classification and machine learn (Andrea Bertozzi, UCLA) -
- An improved bound on sums of square roots via the subspace theorem (Friedrich Eisenbrand, EPFL) -
- Information complexity of mixed-integer convex optimization (Amitabh Basu, Johns Hopkins University) -