Holland Matthew J.

ホーランドマシュー | Holland Matthew J.

Affiliation and department：
Job title： Assistant Professor

Research keywords (2)： Statistical learning theory , Machine learning

Research theme for competitive and other funds (9)：

2022 - 2026 Novel learning algorithms through off-sample generalization metric design
2021 - 2025 Machine learning with guarantees under diverse risk measures
2022 - 2022 Designing new learning algorithms via novel feedback generation mechanisms
2020 - 2022 Learning with guarantees under more diverse notions of risk
2019 - 2022 Robust and efficient learning algorithms through control of margin distributions

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Papers (23)：

Matthew J. Holland. Robust variance-regularized risk minimization with concomitant scaling. AISTATS 2024 (to appear). 2024
Matthew J. Holland. Criterion collapse and loss distribution control. arXiv preprint. 2024
Matthew J. Holland, Kazuki Tanabe. A Survey of Learning Criteria Going Beyond the Usual Risk. Journal of Artificial Intelligence Research. 2023. 78. 781-821
Matthew J. Holland, Kosuke Nakatani. Implicit regularization via soft ascent-descent. arXiv preprint. 2023
Matthew J. Holland. Flexible risk design using bi-directional dispersion. Proceedings of Machine Learning Research (AISTATS 2023). 2023. 206. 1586-1623

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MISC (2)：

Matthew J. Holland. 5分で分かる!? 有名論文ナナメ読み:Duchi, J. et al. : Adaptive Subgradient Methods for Online Learning and Stochastic Optimization. IPSJ Magazine. 2019. 60. 8. 780-781
Matthew J. Holland. Robust gradient descent via back-propagation: A Chainer-based tutorial. 2019

Works (13)：

collapse: a study of criterion collapse in machine learning
Matthew J. Holland 2024 -
bdd-flood: links between bi-directional dispersion and flooding
Matthew J. Holland 2023 -
bdd-mv: mean-variance minimization using bi-directional dispersion functions
Matthew J. Holland 2023 -
offgen: a visual "explainer" for off-sample generalization metrics
Matthew J. Holland 2022 -
bdd: bidirectional dispersion and risk function design
Matthew J. Holland 2022 -

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Professional career (1)：

Awards (7)：

2023/07 - Transactions on Machine Learning Research (TMLR) Expert Reviewer
2022/07 - Japanese Neural Network Society Distinguished Presentation Award (NEURO2022)
2021/09 - Japanese Neural Network Society Young Researcher Award (JNNS2021)
2019/11 - IEICE, Information-Based Induction Sciences and Machine Learning (IBISML) Technical Committee Award finalist (IBIS 2019)
2018/03 - Foundation for NAIST NAIST Top Student Award (PhD Program)

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