[Makoto Yamada] Nonlinear machine learning for scientific discovery

PRESTO Researcher

Makoto Yamada

Makoto Yamada

RIKEN
Center for Advanced Intelligence Project
Unit Leader

Outline

In this project, we will develop a machine learning algorithm for scientific discovery. More specifically, we will develp a nonlinear feature selection algorithm for high-dimensional big data based on sparse modeling techniques. We plan to apply the proposed algorithms for a number of applications including biomarker detection and material discovery.

Quick Access

Quick Access

 News

arrow On-going

arrow Completed

Program

  • CREST
  • PRESTO
  • ACT-I
  • ERATO
  • ACT-C
  • ACCEL
  • ALCA
  • RISTEX
Finish programs
  • Pamphlet
  • ProjectDB
  • GlobalActivity
  • Diversity-EN
  • OS_Policy-EN
  • Question-E