Tokyo Probability Seminar

Seminar information archive ~07/17Next seminarFuture seminars 07/18~

Date, time & place Monday 16:00 - 17:30 Room #126 (Graduate School of Math. Sci. Bldg.)
Organizer(s) Makiko Sasada, Naoki Kubota, Yoshihiro Abe

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2018/07/30

16:00-17:30   Room #126 (Graduate School of Math. Sci. Bldg.)
Tomohiro Hayase (Graduate School of Mathematical Sciences, The University of Tokyo)
Parameter estimation of random matrix models via free probability theory (JAPANESE)
[ Abstract ]
For random matrix models, the parameter estimation based on the likelihood is not straightforward in particular when there is only one sample matrix. We introduce a new parameter optimization method of random matrix models which works even in such a case not based on the likelihood, instead based on the spectral distribution. We use the spectral distribution perturbed by Cauchy noises because the free deterministic equivalent, which is a tool in free probability theory, allows us to approximate it by a smooth and accessible density function.
In addition, we propose a new rank recovery method for the signal-plus-noise model, and experimentally demonstrate that it recovers the true rank even if the rank is not low; It is a simultaneous rank recovery and parameter estimation procedure.
[ Reference URL ]
http://www.ms.u-tokyo.ac.jp/~hayase/