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HOLLAND Matthew James  HOLLAND Matthew・James

… Alternative Names

Holland Matthew J.  HOLLAND Matthew・James

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Researcher Number 00810227
Other IDs
  • ORCIDhttps://orcid.org/0000-0002-6704-1769
Affiliation (Current) 2025: 関西大学, ビジネスデータサイエンス学部, 准教授
Affiliation (based on the past Project Information) *help 2019 – 2024: 大阪大学, 産業科学研究所, 助教
2018: 大阪大学, データビリティフロンティア機構, 特任助教(常勤)
Review Section/Research Field
Principal Investigator
Basic Section 61030:Intelligent informatics-related / 1002:Human informatics, applied informatics and related fields
Keywords
Principal Investigator
確率的最適化 / 機械学習 / 統計的学習理論
  • Research Projects

    (3 results)
  • Research Products

    (13 results)
  •  Novel learning algorithms through off-sample generalization metric designPrincipal Investigator

    • Principal Investigator
      HOLLAND Matthew・James
    • Project Period (FY)
      2022 – 2025
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 61030:Intelligent informatics-related
    • Research Institution
      Osaka University
  •  Robust and efficient learning algorithms through control of margin distributionsPrincipal Investigator

    • Principal Investigator
      Holland Matthew J.
    • Project Period (FY)
      2019 – 2021
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 61030:Intelligent informatics-related
    • Research Institution
      Osaka University
  •  Robust and efficient learning algorithms through control of margin distributionsPrincipal Investigator

    • Principal Investigator
      HOLLAND Matthew・James
    • Project Period (FY)
      2018 – 2019
    • Research Category
      Grant-in-Aid for Research Activity Start-up
    • Review Section
      1002:Human informatics, applied informatics and related fields
    • Research Institution
      Osaka University

All 2024 2023 2022 2021 2019

All Journal Article Presentation

  • [Journal Article] Robust variance-regularized risk minimization with concomitant scaling2023

    • Author(s)
      Matthew J. Holland
    • Journal Title

      arXiv preprint

      Volume: 1 Pages: 1-27

    • Open Access
    • Data Source
      KAKENHI-PROJECT-23K24902
  • [Journal Article] Anytime Guarantees Under Heavy-Tailed Data2022

    • Author(s)
      Matthew J. Holland
    • Journal Title

      Proceedings of the AAAI Conference on Artificial Intelligence

      Volume: -

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Journal Article] Spectral risk-based learning using unbounded losses2022

    • Author(s)
      Matthew J. Holland, El Mehdi Haress
    • Journal Title

      Proceedings of Machine Learning Research

      Volume: -

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Presentation] Robust variance-regularized risk minimization with concomitant scaling2024

    • Author(s)
      Matthew J. Holland
    • Organizer
      AISTATS 2024
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K24902
  • [Presentation] 損失の期待値と分散をロバストに最小化する学習法2023

    • Author(s)
      Matthew J. Holland
    • Organizer
      人工知能学会全国大会 (第37回)
    • Data Source
      KAKENHI-PROJECT-23K24902
  • [Presentation] Anytime Guarantees Under Heavy-Tailed Data2022

    • Author(s)
      Matthew J. Holland
    • Organizer
      AAAI 2022
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Presentation] Spectral risk-based learning using unbounded losses2022

    • Author(s)
      Matthew J. Holland, El Mehdi Haress
    • Organizer
      AISTATS 2022
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Presentation] Robustness and scalability under heavy tails, without strong convexity2021

    • Author(s)
      Matthew J. Holland
    • Organizer
      AISTATS 2021
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Presentation] Learning with risk-averse feedback under potentially heavy tails2021

    • Author(s)
      Matthew J. Holland
    • Organizer
      AISTATS 2021
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Presentation] Scaling-Up Robust Gradient Descent Techniques2021

    • Author(s)
      Matthew J. Holland
    • Organizer
      AAAI 2021
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Presentation] Classification using margin pursuit2019

    • Author(s)
      Matthew J. Holland
    • Organizer
      AISTATS 2019
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18H06477
  • [Presentation] Classification using margin pursuit2019

    • Author(s)
      Matthew J. Holland
    • Organizer
      AISTATS 2019
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342
  • [Presentation] PAC-Bayes under potentially heavy tails2019

    • Author(s)
      Matthew J. Holland
    • Organizer
      NeurIPS 2019
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-19K20342

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