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深圳大学高等研究院是深圳大学于2014年成立的一个包含本科与研究生培养、侧重跨学科教学与学术研究的校内综合办学单位。作为深圳大学内部探索全面改革创新的学术特区,高等研究院与香港和海外著名高校合作,借鉴国内外研究型大学通行的管理模式,引进具有一流视野的资深教授和发展潜力的青年教师,营造与国际接轨的学术氛围和培养环境,开展卓越的教学、研究和管理工作。

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高等研究院系列学术讲座一百二十五

发布时间:2020-10-12 | 浏览次数:

A Contour-integral Based Method for Generalized Eigenvalue Problems

Speaker Dr. Guojian Yin

Hong Kong University of Science and Technology


About the Speaker

Dr. Yin received his PhD degree in mathematics from the Chinese University of Hong Kong. He is now a postdoctoral fellow at the Hong Kong University of Science and Technology. Dr. Yin’s research interests include developing efficient algorithms for large-scale eigenvalue problems, low-rank matrix/Tensor completion and RPCA, machine learning, etc.


Talk Introduction

The contour-integral based eigensolvers are the recent efforts for computing the eigenvalues inside a given region in the complex plane. The best-known members are the Sakurai-Sugiura (SS) method, and the FEAST algorithm. An attractive computational advantage of these methods is that they are easily parallelizable. The FEAST algorithm was developed for the generalized Hermitian eigenvalue problems. It is stable and accurate. However, it may fail when applied to non-Hermitian problems. In this talk, we will introduce a generalized FEAST algorithm, which aims to extend FEAST to the non-Hermitian problems. Our approach can be summarized as follows: (i) construct a particular contour integral to form a search subspace containing the desired eigenspace, and (ii) use the oblique projection technique to extract desired eigenpairs with appropriately chosen test subspace. In addition, in the talk, a contour-integral based method for counting the eigenvalues inside a given region will be introduced.


时间:2020年10月14日14:30-15:30

地点:汇元楼(原办公楼)103会议室

All are welcome!