Thursday, February 15, 2018 11 a.m. to noon

Fast and stable algorithms for large-scale computation

 Dr. Yuanzhe Xi

Department of Computer Science and Engineering

University of Minnesota

 Abstract:  Scientific computing and data analytics have become the third and fourth pillars of scientific discovery. Their success is tightly linked to a rapid increase in the size and complexity of problems and datasets of interest. In this talk, I will discuss our recent efforts in the development of novel numerical algorithms for tackling these challenges. In the first part, I will present a stochastic Lanczos algorithm for estimating the spectrum of Hermitian matrix pencils. The proposed algorithm only accesses the matrices through matrix-vector products and is suitable for large-scale computations. This algorithm is one of the key ingredients in the new breed of “spectrum slicing”-type eigensolvers for electronic structure calculations. In the second part, I will present our newly developed fast structured direct solvers for kernel systems and its applications in accelerating the learning process. By exploiting intrinsic low-rank property associated with the coefficient matrix, these structured solvers could overcome the cubic solution cost and quadratic storage cost of standard dense direct solvers and provide a new framework for performing various matrix operations in linear complexity. 

Location:

Mathematical Sciences Building: 318

Contact:

Constance Schober constance.schober@ucf.edu

Calendar:

Mathematics Department Calendar

Category:

Speaker/Lecture/Seminar

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