Rchr
J-GLOBAL ID:201201034649653220   Update date: Jun. 14, 2024

Sugiyama Masashi

スギヤマ マサシ | Sugiyama Masashi
Affiliation and department:
Job title: Director
Other affiliations (1):
Homepage URL  (2): http://www.ms.k.u-tokyo.ac.jp/sugi/index-jp.htmlhttp://www.ms.k.u-tokyo.ac.jp/sugi/
Research field  (1): Intelligent informatics
Research theme for competitive and other funds  (16):
  • 2020 - 2023 Theory for unified expression of recognition mechanisms and its application to machine learning
  • 2017 - 2022 Theory and Application of Statistical Reinforcement Learning
  • 2017 - 2020 Theory of operator manifold and its application to pattern recognition
  • 2014 - 2017 Manifold signal processing theory concerning metric structure and its application to biological signal processing
  • 2013 - 2017 Theory and Application of Information-Based Machine Learning
Show all
Papers (556):
  • Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama. BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning. CoRR. 2023. abs/2305.18377
  • Jingfeng Zhang, Bo Song, Bo Han 0003, Lei Liu, Gang Niu 0001, Masashi Sugiyama. Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks. CoRR. 2023. abs/2305.00399
  • Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli. Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization. CoRR. 2023. abs/2305.00374
  • Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli. Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection. CoRR. 2023. abs/2302.03857
  • Salah Ghamizi, Jingfeng Zhang, Maxime Cordy, Mike Papadakis, Masashi Sugiyama, Yves Le Traon. GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks. CoRR. 2023. abs/2302.02907
more...
MISC (255):
  • Motoya Ohnishi, Gennaro Notomista, Masashi Sugiyama, Magnus Egerstedt. Constraint learning for control tasks with limited duration barrier functions. Automatica. 2021. 127. 109504-109504
  • Takuya Shimada, Han Bao, Issei Sato, Masashi Sugiyama. Classification from Pairwise Similarities/Dissimilarities and Unlabeled Data via Empirical Risk Minimization. Neural computation. 2021. 33. 5. 1-35
  • 江間 有沙, 木谷 強, 石黒 浩, 杉山 将, 西野 恒, 田丸 健三郎, Papaspyridis Alexandros. パネルディスカッション AIの社会実装とAI人材の育成に向けて必要なこと : 大学とAIエコシステム (特集 AI活用ができる人材育成に必要な大学変革と役割) -- (AIアカデミックフォーラム2020). 大学マネジメント = University & college management. 2020. 15. 12. 29-33
  • 杉山 将. 世界をリードするAI研究と人材育成への挑戦 (特集 AI活用ができる人材育成に必要な大学変革と役割) -- (AIアカデミックフォーラム2020). 大学マネジメント = University & college management. 2020. 15. 12. 19-24
  • OTSUBO Yosuke, OTANI Naoya, CHIKASUE Megumi, SUGIYAMA Masashi. Failure factor detection in production process. Proceedings of the Annual Conference of JSAI. 2020. 2020. 0. 2I4GS204-2I4GS204
more...
Books (14):
  • ディープラーニングG検定ジェネラリスト問題集
    インプレス 2019 ISBN:9784295005667
  • Variational Bayesian learning theory
    Cambridge University Press 2019 ISBN:9781107076150
  • ベイズ推論による機械学習入門 = Introduction to machine learning by Bayesian inference
    講談社 2017 ISBN:9784061538320
  • 異常検知と変化検知 = Anomaly detection and change detection
    講談社 2015 ISBN:9784061529083
  • 機械学習のための確率と統計 = Probability and statistics for machine learning
    講談社 2015 ISBN:9784061529014
more...
Professional career (1):
  • Doctor of Engineering (Tokyo Institute of Technology)
Work history (2):
  • 2016/07 - 現在 RIKEN Center for Advanced Intelligence Project Director
  • 2014/10 - 現在 The University of Tokyo Graduate School of Frontier Sciences Professor
※ Researcher’s information displayed in J-GLOBAL is based on the information registered in researchmap. For details, see here.

Return to Previous Page