Qibin Zhao (Ph.D.)
Title
Team Leader

Members

  • Team leader
    Qibin Zhao
  • Research scientist
    Chao Li
  • Postdoctoral researcher
    Andong Wang
  • Postdoctoral researcher
    Jianfu Zhang
  • Senior visiting scientist
    A Cichocki
  • Visiting scientist
    Toshihisa Tanaka
  • Visiting scientist
    Tatsuya Yokota
  • Visiting scientist
    Xuyang Zhao
  • Visiting scientist
    Jian-ting Cao
  • Junior research associate
    Zerui Tao
  • Part-time worker I
    Linfeng Sui
  • Part-time worker II
    Mo Xia
  • Part-time worker II
    Pengju Zhang
  • Part-time worker II
    Huidong Jiang

Introduction

Laboratory's photo

We study various tensor-based machine learning technologies, e.g., tensor decomposition, multilinear latent variable model, tensor regression and classification, tensor networks, deep tensor learning, and Bayesian tensor learning, with aim to facilitate the learning from high-order structured data or large-scale latent space. Our goal is to develop innovative, scalable and efficient tensor learning algorithms supported by theoretical principles. The novel applications in computer vision and brain data analysis will also be explored to provide new insights into tensor learning methods.

Main Research Field
Computer Science
Research Field
Engineering / Neuroscience & Behavior / Mathematics
Research Subjects
Tensor Decomposition and Tensor Networks
Bayesian Tensor Learning
Deep Tensor Learning
Laboratory Website URL
RIKEN Website URL

Introduction Video

Poster(s)
Related posts
posted on January 29, 2021 13:48Information
posted on January 27, 2021 11:12Information
posted on July 7, 2020 15:05Information
posted on December 5, 2019 09:30Information
posted on September 11, 2019 12:00Information