Colloquiums (FM & IMI)

The IMI Colloquium in December 2021
Date : Wednesday, 21 December 2021 17:30-18:30
Place : Llive-streaming by Zoom

Speaker : Miki Aoyagi (College of Science and Technology, Nihon University)

Title :
On the learning coefficients in learning theory

Abstract : In recent studies, image or speech recognition, probabilistic inference, genetic analysis, time series prediction, and data mining, etc. In real big data have been analyzed by learning systems. They are very complicated and not usually generated by a simple normal distribution, as they are influenced by many factors. Hierarchical learning models such as layered neural networks, the normal mixture model, and reduced rank regression may be known as effective learning models. They, however, likewise have complicated, i.e., singular structures, which cannot be analyzed using the classic theories of regular statistical models. The theoretical study has therefore been started to construct a mathematical foundation for singular statistical models. In this talk, we consider learning coefficients in learning theory, which serve to measure the main term of learning efficiency in singular learning models. These coefficients have an important role in information criteria and are mathematically equal to the log canonical thresholds which are obtained by using complete de-singularization.

* Notes *

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If you have any questions, please contact Tagami-sensei (E-mail: tagami(at)imi.kyushu-u.ac.jp).