Orthogonality and Oscillation, Sines and Cosines, Sturm and Liouville, Wasserstein and Optimal Transport
Log-concave polynomials, matroids, and expanders
Universality in numerical computation
The speaker will discuss a variety of universality results in numerical computation with random data. It turns out that for many standard algorithms the fluctuations in the time it takes to achieve a given accuracy are universal, independent of the statistical assumptions on the data. Some of the results presented are numerical, and some are analytical.
This is joint work with a number of authors over the last 6 or 7 years, but mostly with Tom Trogdon.
Modeling the Black Hole Image
Computational complexity of approximation and complex zeros
Bridging convex and nonconvex optimization in noisy matrix completion: Stability and uncertainty quantification
Hardness of Approximation
Hardness of Approximation studies the phenomenon that for several fundamental NP-hard problems, even computing approximate solutions to them remains an NP-hard problem. The talk will give an overview of this study along with its connections to algorithms, analysis, and geometry.
Lattice-Based Cryptography and the Learning with Errors Problem
PLEASE NOTE UPDATED LOCATION: JADWIN HALL, ROOM A10
Optimization, Complexity and Math (through the lens of one problem and one algorithm)
I will first introduce and motivate the main characters in this plot: