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Virtual LANS Seminar
January 20, 2021 @ 10:30 - 11:30 CST
Seminar Title: Data-Driven Hierarchical Kernel Matrix Methods
Speaker: Yuanzhe Xi, Assistant Professor, Department of Mathematics, Emory University
Date/Time: January 20, 2021 / 10:30 AM – 11:30 AM
Location: See meeting URL on the cels-seminars website (requires Argonne login)
Description: The explosion of datasets from diverse applications and the increasing computational power of computer hardware call for the need of scalable algorithms and software. In this talk, I will focus on the computational bottlenecks associated with fully populated kernel matrices that are ubiquitous in machine learning as well as scientific simulations. Those dense matrices usually induce large computation costs that scale quadratically or cubically with problem size. The complexity can be significantly reduced by exploiting the hierarchical rank structure inside the kernel matrices. Representing a kernel matrix in an appropriate hierarchical format enables (nearly) optimal storage and computations. I will demonstrate the newly developed data-driven techniques for hierarchical representations and compare their performance with state-of-the-art methods/software on several real-world applications.
Please note that the meeting URL for this event can be seen on the cels-seminars website, which requires an Argonne login.