Qibin Zhao
Qibin Zhao (Ph.D.)
Title
Team Leader

Members

  • Team leader
    Qibin Zhao
  • Research scientist
    Chao Li
  • Postdoctoral researcher
    Andong Wang
  • Postdoctoral researcher
    Jianfu Zhang
  • Postdoctoral researcher
    Reinmar Kobler
  • Postdoctoral researcher
    Vidyadhar Upadhya
  • Senior visiting scientist
    A Cichocki
  • Senior visiting scientist
    Jian-ting Cao
  • Visiting scientist
    Toshihisa Tanaka
  • Visiting scientist
    Tatsuya Yokota
  • Visiting scientist
    Motoaki Kawanabe
  • Visiting scientist
    Xuyang Zhao
  • Visiting scientist
    Keping Yu
  • Junior research associate
    Linfeng Sui
  • Junior research associate
    Zerui Tao
  • Part-time worker II
    Huidong Jiang
  • Part-time worker II
    Jinyu Gu

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

AIP Open Seminar #1: Tensor Learning Team (PI: Qibin Zhao) thumbnails
Poster(s)

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