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讲座信息:Monte Carlo Methods for Numerical Linear Algebra and Their Applications
发表时间:2017-06-29 阅读次数:55次

 

Monte Carlo Methods for Numerical Linear Algebra and Their Applications

Prof. Yaohang Li(Old Dominion University)

 

时  间:2017年7月2日(周日)9:00-12:00, 13:30-16:30
地  点:张江校区微电子楼269会议室

 

Abstract
In the era of “big data,” numerical linear algebra operations related to large matrices are behind many applications, ranging from data mining to large-scale simulations and machine learning. The Monte Carlo methods, which are based on statistical sampling, exhibit many attractive properties, including fast approximated results, memory efficiency, reduced matrix element accesses, and intrinsic parallelism. As a result, there has been a recent increase of interest of using Monte Carlo methods to carry out computations on large matrices.
In this talk, we will present Monte Carlo methods for approximating solutions for problems associated with large matrices, including singular value decompositions, extreme eigenvalues/eigenvectors, matrix-matrix multiplications, and linear systems. These Monte Carlo methods are characterized by fast solution approximation, reduced matrix elements visits, numerical stability, and scalability to modern parallel computing platforms. Applications in computational biology, image segmentation, sport simulation, and HPC fault detection are also discussed.

 

Biography
Dr. Yaohang Li is an Associate Professor in the Department of Computer Science at Old Dominion University. His research interests are in Computational Biology and Scientific Computing. He received the Ph.D. and M.S. degrees in Computer Science from the Florida State University in 2003 and 2000, respectively. After graduation, he worked at Oak Ridge National Laboratory as a research associate. Before joining ODU, he was an associate professor in the Computer Science Department at North Carolina A&T State University. He is the recipient of Ralph E. Powe Award and NSF CAREER Award.

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