[Kei Kobayashi] Statistial Analysis and Theory via Geometric Features of Data Spaces

Presto Researcher

小林 景

Kei Kobayashi

Keio University
Associate Professor
website

Outline

Some statistical analysis methods use the information of the curvature of a manifold or a polyhedral complex on which data are distributed. Such geometric objects, called data spaces play a role to improve the capacity of the statistical analysis especially when the data has specific structures including “big data,” and has been drawing attention on various application fields. In this research project, we will evaluate geometric features of data spaces such as the curvature theoretically. Furthermore, we will consider some deformations of data spaces in order to develop novel methods for statistical analysis.

Quick Access

Program

  • CREST
  • PRESTO
  • ACT-I
  • ERATO
  • ACT-C
  • ACCEL
  • ALCA
  • RISTEX
  • AIP Network Lab
  • JST ProjectDB
  • Global Activities
  • Diversity
  • OSpolicy
  • Yuugu
  • Questions