Laplacian Paradigm 2.0: Merging Continuous and Discrete

Richard Peng (GaTech) 08:40 -- 09:10

Over the past three decades, works related to efficient solvers for a class of graph structured matrices, graph Laplacians, led to fundamental results in combinatorial optimization and scientific computing as well as the Laplacian paradigm for graph algorithms. In this talk I’ll survey these progresses, with focus on the underlying algorithm design approaches. Specifically, I will discuss the origin of the Laplacian paradigm in combining combinatorial and numerical building blocks via spectral graph theory, and describe recent efforts on designing new tools tailored towards the overall algorithmic questions.