Reproducing kernel Hilbert spaces have developed into an important tool in many areas, especially statistics and machine learning, and they play a valuable role in complex analysis, probability, group representation theory, and the theory of integral operators. This course will offer a unified overview providing detailed examples of applications, as well as covering the fundamental underlying theory, including chapters on interpolation and approximation, Cholesky and Schur operations on kernels, and vector-valued spaces. Prerequisites: 4111-4112. Suggested: 5051-52.
Section 01Topics in Analysis
INSTRUCTOR: BongersView Course Listing