Seeking solid-wave solitons in resonant MEMS
Theory and scalable algorithms for kernel-based function approximation.
Asynchronous parallel algorithms for finding minima fast by fitting functions to surrogate models.
Fast spectral tools for graph structure.
Numerical Methods for Data Science (CS 6241)
Discussion of numerical methods in the context of machine learning and data analysis problems. We will discuss sparsity, rank structure, and spectral behavior of underlying linear algebra problems; convergence behavior and implicit regularization for standard solvers; and comparisons between numerical methods in data analysis and those used in physical simulations.
SCAN Seminar (CS/MATH 7290)
Ongoing. M 1:25-2:15.
The Scientific Computing and Numerics seminar series focuses on various methods in scientific computing, the analysis of convergence properties and computational efficiency, and their adaptation to specific applications.