Taiji Suzuki
Taiji Suzuki (Ph.D.)
Team Leader


  • Team leader
    Taiji Suzuki
  • Senior research scientist
    Sho Sonoda
  • Research scientist
    Wei Huang
  • Postdoctoral researcher
    Stefano Massaroli
  • Visiting scientist
    Takafumi Kanamori
  • Visiting scientist
    Takashi Takenouchi
  • Visiting scientist
    Hironori Fujisawa
  • Visiting scientist
    Shotaro Akaho
  • Visiting scientist
    Takayuki Kawashima
  • Visiting scientist
    Yuichiro Wada
  • Visiting scientist
    Noboru Murata
  • Junior research associate
    Takumi Nakagawa
  • Part-time worker I
    Kosaku Takanashi
  • Part-time worker I
    Toshinori Kitamura
  • Part-time worker II
    Kazusato Oko
  • Part-time worker II
    Fumiya Uchiyama
  • Part-time worker II
    Kei Tsukamoto
  • Part-time worker II
    Yuya Fujisaki
  • Part-time worker II
    Juno Kim
  • Part-time worker II
    Ryotaro Kawata


Laboratory's photo

Our team, deep learning theory team, is studying various kinds of learning systems including deep learning from theoretical viewpoints. We enrich our understandings of complex learning systems, and leverage the insights to construct new machine learning techniques and apply them. Especially, machine learning should deal with high dimensional and complicated data, and thus we are studying deep learning and structured sparse learning as methods to deal with such complicated data. Moreover, we are also developing efficient optimization algorithms for large and complicated machine learning problems based on such techniques as stochastic optimization.

Main Research Field
Computer Science
Research Field
Research Subjects
Statistical learning theory of wide range of learning systems including deep learning
Efficient optimization algorithm for large dataset
High dimensional statistics

Introduction Video

Talk by Takuo Matsubara, Newcastle University/Alan Turing Institute<br> on Robust Generalised Bayesian Inference for Intractable Likelihoods thumbnails

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