Makoto Yamada (Ph.D.)
Title
Unit Leader

Members

  • Unit Leader
    Makoto Yamada
  • Postdoctoral Researcher
    Tam Thanh Le
  • Senior Visiting Scientist
    Kenji Fukumizu
  • Senior Visiting Scientist
    Shigeyuki Matsui
  • Visiting Scientist
    Taichiro Endo
  • Visiting Scientist
    Masaaki Imaizumi
  • Visiting Scientist
    Yuta Itoh
  • Visiting Scientist
    Benjamin Poignard
  • Technical Staff I
    Dinesh Singh

Introduction

Laboratory's photo

We are focusing on developing machine learning algorithm for large p and small n problems such as biomarker discovery and toxicogenomics prediction. In particular, we are interested in nonlinear feature selection algorithms for such high-dimensional data, and proposing simple yet efficient algorithms. Ultimately, we want to build a machine learning framework to automatically find an important information from data.

Main Research Field
Computer Science
Research Subjects
High-dimensional Feature Selection
Transfer Learning
Laboratory Website URL
https://riken-yamada.github.io/
RIKEN Website URL
http://www.riken.jp/en/research/labs/aip/generic_tech/highdim_stat_model/

[Poster] FY2018 Research Results (Written in Japanese)

Related posts
posted on May 16, 2019 13:52Information
Fourteen papers have been accepted at ICML 2019
posted on April 2, 2019 09:32Award
Visiting Scientist Yuta Itoh nominated for the IEEE VR 2019 Best Journal Paper
posted on February 25, 2019 11:22Award
Unit Leader Yamada received Outstanding Senior Program Committee Award at WSDM2019
posted on September 7, 2018 17:55Information
Twelve papers are accepted at NeurIPS 2018
posted on April 20, 2018 11:39Award
Visiting Scientist Yuta Itoh to receive Honorable Mention Award at CHI 2018
posted on April 11, 2018 16:28Award
Masaaki Imaizumi and Takanori Maehara receive AISTATS 2018 Best Paper Award