第20回統計的機械学習セミナー / The 20th Statistical Machine Learning Seminar
- Date&Time
- 2014年10月3日（金）15：00－
/ 3 October, 2014 (Fri) 15：00－
- Place
- 統計数理研究所 セミナー室5（3階D313）
/ Seminar Room 5（D313）@ The Institute of Statistical Mathematics
- Title
- Riemannian geometry and matrix geometric means
- Speaker
- Professor Rajendra Bhatia
Indian Statistical Institute, New Delhi
- Abstract
- Positive definite matrices are used in several areas of mathematics, physics, statistics and engineering. Often it is required to define an average of several such matrices that must have some properties dictated by the problem. One such average is the geometric mean. For two positive definite matrices the concept was introduced and studied long ago. For more than two matrices a good definition (based on Riemannian geometry) was given only ten years ago. Since then there have been many interesting developments, and the concept has found many applications. In this talk we will survey these ideas.
