Updated on 2025/03/25

Information

 

写真a

 
KURATA SUMITO
 
Organization
Institute of Mathematics for Industry Division of Industrial and Mathematical Statistics Assistant Professor
School of Sciences Department of Mathematics(Concurrent)
Graduate School of Mathematics Department of Mathematics(Concurrent)
Title
Assistant Professor
Profile
例えば突出した能力、例えば災害級の現象、例えば観測機器の故障、例えば人的なミス、等々、現実のデータには様々な由来を持った「外れ値」、全体から外れた値を取るデータが付き物です。この外れ値には明確な定義や線引きを与えることが難しく、また発生を防ぐことも事実上不可能です。その為、外れ値が混ざっていてもその影響を小さく抑えられる「頑健(ロバスト)」な手法というのが、分析において重要な意味を持つと考えられます。私は、モデル選択を中心に、頑健な分析手法について研究を行っています。確率分布間の遠さを測る尺度である統計的ダイバージェンスで、モデルと根底に在る「真の分布」との「近さ」を検証し、文理を問わない幅広い分野にて現象や行動を適切に表現出来るモデルを探ります。また、教育活動においてはこれまでの経験を活かし、学部・学府での教育と併せて、学外・社会人に向けた講座等、統計学を中心とした発信にも積極的に取り組んでゆきたいと考えております。
External link

Degree

  • Doctor of Science (OSAKA UNIVERSITY)

  • Master of Engineering (OSAKA UNIVERSITY)

Research History

  • 東京大学 情報理工学系研究科 特任助教   

Research Interests・Research Keywords

  • Research theme: On model selection criteria based on statistical divergence measures

    Keyword: Statistical Science, Model Selection, Robustness

    Research period: 2016.4

Papers

  • On robustness of model selection criteria based on divergence measures: Generalizations of BHHJ divergence-based method and comparison Reviewed International journal

    Kurata, S.

    Communications in Statistics - Theory and Methods   53 ( 10 )   3499 - 3516   2024.4

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Communications in Statistics - Theory and Methods  

    In model selection problems, robustness is one important feature for selecting an adequate model from the candidates. We focus on statistical divergence-based selection criteria and investigate their robustness. We mainly consider BHHJ divergence and related classes of divergence measures. BHHJ divergence is a representative robust divergence measure that has been utilized in, for example, parametric estimation, hypothesis testing, and model selection. We measure the robustness against outliers of a selection criterion by approximating the difference of values of the criterion between the population with outliers and the non-contaminated one. We derive and compare the conditions to guarantee robustness for model selection criteria based on BHHJ and related divergence measures. From the results, we find that conditions for robust selection differ depending on the divergence families, and that some expanded classes of divergence measures require stricter conditions for robust model selection. Moreover, we prove that robustness in estimation does not always guarantee robustness in model selection. Through numerical experiments, we confirm the advantages and disadvantages of each divergence family, asymptotic behavior, and the validity for employing criteria on the basis of robust divergence. Especially, we reveal the superiority of BHHJ divergence in robust model selection for extensive cases.

    DOI: 10.1080/03610926.2022.2155788

    Scopus

    Other Link: https://www.tandfonline.com/doi/full/10.1080/03610926.2022.2155788

    Repository Public URL: https://hdl.handle.net/2324/7172132

  • Structured regularization based velocity structure estimation in local earthquake tomography for the adaptation to velocity discontinuities

    Yamanaka Y., Kurata S., Yano K., Komaki F., Shiina T., Kato A.

    Earth, Planets and Space   74 ( 1 )   2022.12   ISSN:13438832

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Earth, Planets and Space  

    We propose a local earthquake tomography method that applies a structured regularization technique to determine sharp changes in Earth’s seismic velocity structure using arrival time data of direct waves. Our approach focuses on the ability to better image two common features that are observed in Earth’s seismic velocity structure: sharp changes in velocities that correspond to material boundaries, such as the Conrad and Moho discontinuities; and gradual changes in velocity that are associated with pressure and temperature distributions in the crust and mantle. We employ different penalty terms in the vertical and horizontal directions to refine the earthquake tomography. We utilize a vertical-direction (depth) penalty that takes the form of the l1-sum of the l2-norms of the second-order differences of the horizontal units in the vertical direction. This penalty is intended to represent sharp velocity changes caused by discontinuities by creating a piecewise linear depth profile of seismic velocity. We set a horizontal-direction penalty term on the basis of the l2-norm to express gradual velocity tendencies in the horizontal direction, which has been often used in conventional tomography methods. We use a synthetic data set to demonstrate that our method provides significant improvements over velocity structures estimated using conventional methods by obtaining stable estimates of both steep and gradual changes in velocity. We also demonstrate that our proposed method is robust to variations in the amplitude of the velocity jump, the initial velocity model, and the number of observed arrival times, compared with conventional approaches, and verify the adaptability of the proposed method to dipping discontinuities. Furthermore, we apply our proposed method to real seismic data in central Japan and present the potential of our method for detecting velocity discontinuities using the observed arrival times from a small number of local earthquakes. Graphical Abstract: [Figure not available: see fulltext.].

    DOI: 10.1186/s40623-022-01600-x

    Scopus

  • Statistical modeling for temporal dominance of sensations data incorporating individual characteristics of panelists: an application to data of milk chocolate

    Kurata S., Kuroda R., Komaki F.

    Journal of Food Science and Technology   59 ( 6 )   2420 - 2428   2022.6   ISSN:00221155

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Journal of Food Science and Technology  

    We discuss the modeling of temporal dominance of sensations (TDS) data, time series data appearing in sensory analysis, that describe temporal changes of the dominant taste in the oral cavity. Our aims were to obtain the transition process of attributes (tastes and mouthfeels) in the oral cavity, to express the tendency of dominance durations of attributes, and to specify factors (such as sex, age, food preference, dietary habits, and sensitivity to a particular taste) affecting dominance durations, simultaneously. To achieve these aims, we propose an analysis procedure applying models based on the semi-Markov chain and the negative binomial regression, one of the generalized linear models. By using our method, we can take differences among individual panelists and dominant attributes into account. We analyzed TDS data for milk chocolate with the proposed method and verified the performance of our model compared with conventional analysis methods. We found that our proposed model outperformed conventional ones; moreover, we identified factors that have effects on dominance durations. Results of an experiment support the importance of reflecting characteristics of panelists and attributes.

    DOI: 10.1007/s13197-021-05260-9

    Scopus

  • Detection of low-frequency earthquakes by the matched filter technique using the product of mutual information and correlation coefficient Reviewed International journal

    Kurihara, R., Kato, A., Kurata, S., Nagao, H.

    Earth, Planets and Space   73   2021.12

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1186/s40623-021-01534-w

  • Graph-partitioning based convolutional neural network for earthquake detection using a seismic array Reviewed International journal

    Yano, K., Shiina, T., Kurata, S., Kato, A., Komaki, F., Sakai, S. I., Hirata, N.

    Journal of Geophysical Research: Solid Earth   126 ( 5 )   2021.4

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1029/2020JB020269

  • On the consistency and the robustness in model selection criteria Reviewed International journal

    Kurata, S., Hamada, E.

    Communications in Statistics - Theory and Methods   49 ( 21 )   5175 - 5195   2020.11

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1080/03610926.2019.1615093

  • A discrete probabilistic model for analyzing pairwise comparison matrices Reviewed International journal

    Kurata, S., Hamada, E.

    Communications in Statistics - Theory and Methods   48 ( 15 )   3801 - 3815   2019.8

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1080/03610926.2018.1481975

    Other Link: https://www.tandfonline.com/doi/full/10.1080/03610926.2018.1481975

    Repository Public URL: https://hdl.handle.net/2324/7179469

  • AHP・ANPの一対比較行列に対する統計的解析手法の検討

    倉田澄人, 濵田悦生

    京都大学数理解析研究所講究録   2078   166 - 172   2018.7

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Research paper (other academic)  

  • A robust generalization and asymptotic properties of the model selection criterion family Reviewed International journal

    Kurata, S., Hamada, E.

    Communications in Statistics - Theory and Methods   47 ( 3 )   532 - 547   2018.2

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1080/03610926.2017.1307405

    Other Link: https://www.tandfonline.com/doi/abs/10.1080/03610926.2017.1307405

    Repository Public URL: https://hdl.handle.net/2324/7179470

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Presentations

  • スパース正則化に対する頑健性と選択一致性を備えたモデル評価規準について

    倉田澄人, 廣瀨慧

    統計関連学会連合大会  2024.9 

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    Event date: 2024.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:東京理科大学   Country:Japan  

  • 統計的分析を破綻させる外れ値と、外れ値に耐えるダイバージェンスについて

    倉田澄人

    国際数理科学協会「統計的推測と統計ファイナンス」分科会研究集会  2024.8 

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    Event date: 2024.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:大阪公立大学   Country:Japan  

  • 統計的ダイバージェンスを応用した高次元線形回帰モデルに対する正則化パラメータの頑健な選択について

    倉田澄人, 廣瀨慧

    統計関連学会連合大会  2023.9 

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    Event date: 2023.9 - 2024.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:京都大学, 京都府   Country:Japan  

  • スパース正則化における頑健なモデル選択規準について

    倉田澄人, 廣瀨慧

    国際数理科学協会「統計的推測と統計ファイナンス」分科会研究集会  2023.8 

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    Event date: 2023.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:大阪公立大学, 大阪府   Country:Japan  

  • マルコフ連鎖と一般化線形モデルによるTDSデータの分析について Invited

    倉田澄人

    日本官能評価学会企業部会第105回定例会  2023.3 

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    Event date: 2023.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:ハイブリッド開催(キリンホールディングス飲料未来研究所&オンライン)   Country:Japan  

  • 地下の速度構造変化を捉えるスパース正則化を用いた地震波速度トモグラフィ

    倉田澄人

    iSeisBayes最終報告会  2023.2 

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    Event date: 2023.2

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:東京大学   Country:Japan  

  • 統計的ダイバージェンスと外れ値に対し頑健なモデル選択規準について

    倉田澄人

    統計科学セミナー(九州大学)  2022.10 

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    Event date: 2022.10

    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

    Venue:九州大学 伊都キャンパス   Country:Japan  

  • 外れ値に対して頑健なモデル評価規準の発展可能性: 並立可能な統計学的性質について

    倉田澄人

    統計関連学会連合大会  2022.9 

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    Event date: 2022.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:成蹊大学、オンライン   Country:Japan  

  • 正則化による地震波速度推定精度の改善と構造変化の検出について

    倉田澄人, 山中遥太, 矢野恵佑, 駒木文保, 椎名高裕, 加藤愛太郎

    統計関連学会連合大会  2022.9 

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    Event date: 2022.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:成蹊大学、オンライン   Country:Japan  

  • 構造正則化を用いた地震波速度トモグラフィの性能検証

    倉田澄人, 山中遥太, 矢野恵佑, 駒木文保, 椎名高裕, 加藤愛太郎

    JpGU2022  2022.5 

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    Event date: 2022.5 - 2022.6

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:幕張メッセ(千葉県)、オンライン   Country:Japan  

  • 構造正則化を応用した地震波トモグラフィ法による速度不連続面の検出

    倉田澄人, 山中遥太, 矢野恵佑, 駒木文保, 椎名高裕, 加藤愛太郎

    日本地震学会2021年度秋季大会  2021.10 

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    Event date: 2021.10

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • 頑健性を持つダイバージェンスの拡張とモデル評価規準

    倉田澄人

    統計関連学会連合大会  2021.9 

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    Event date: 2021.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • 地震波速度不連続面の検出のためのスパース正則化に基づく地震波トモグラフィ Invited

    倉田澄人, 山中遥太, 矢野恵佑, 駒木文保, 椎名高裕, 加藤愛太郎

    統計関連学会連合大会  2021.9 

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    Event date: 2021.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • 相互情報量と相関係数の積を用いたマッチドフィルタ法による深部低周波地震の検出

    栗原亮, 加藤愛太郎, 倉田澄人, 長尾大道

    統計関連学会連合大会  2021.9 

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    Event date: 2021.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • 速度不連続面を考慮した地震波速度トモグラフィに対する構造正則化の応用

    倉田澄人, 山中遥太, 矢野恵佑, 駒木文保, 椎名高裕, 加藤愛太郎

    JpGU2021  2021.6 

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    Event date: 2021.5 - 2021.6

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • 評価者側の特性を考慮したTDSデータの新規解析手法の開発

    黒田玲子, 倉田澄人, 駒木文保

    日本官能評価学会 2020年大会  2020.11 

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    Event date: 2020.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • On statistical methods for TDS data analysis: Consideration about characteristics of each panelist and each taste International conference

    Sumito Kurata, Reiko Kuroda, Fumiyasu Komaki

    Sensometrics 2020  2020.10 

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    Event date: 2020.10

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online   Country:Other  

  • 構造正則化に基づく地震波トモグラフィ

    山中遥太, 倉田澄人, 矢野恵佑, 駒木文保, 椎名高裕, 加藤愛太郎

    統計関連学会連合大会  2020.9 

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • ダイバージェンスに基づくBIC型評価規準族について

    倉田澄人

    統計関連学会連合大会  2020.9 

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • 評価者特性を反映した経時的優位感覚データの解析

    倉田澄人, 黒田玲子, 駒木文保

    統計関連学会連合大会  2020.9 

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    Event date: 2020.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:オンライン   Country:Other  

  • A Bayesian seismic tomography adapted to discontinuities International conference

    Sumito Kurata, Naoya Takakura, Keisuke Yano, Fumiyasu Komaki

    JpGU-AGU Joint Meeting 2020  2020.7 

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    Event date: 2020.7

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online   Country:Other  

  • A hidden Markov model for overlapping of seismic waves International conference

    Sumito Kurata, Keisuke Yano, Fumiyasu Komaki

    JpGU-AGU Joint Meeting 2020  2020.7 

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    Event date: 2020.7

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Online   Country:Other  

  • 隠れマルコフモデルを応用した地震データの解析について

    倉田澄人

    第2回 固体地球データ同化に関する研究会  2020.2 

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    Event date: 2020.2

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:東北大学   Country:Japan  

  • 尤度関数の一般化とモデル選択手法の性質

    倉田澄人

    統計関連学会連合大会  2019.9 

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    Event date: 2019.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:滋賀大学   Country:Japan  

  • Local Earthquake Tomography Using Structured Sparsity Regularization for Seismic Velocity Modeling International conference

    Yohta Yamanaka, Keisuke Yano, Fumiyasu Komaki, Sumito Kurata, Aitaro Kato

    StatSei11 (11th International Workshop on Statistical Seismology)  2019.8 

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    Event date: 2019.8

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Hakone   Country:Japan  

  • モデル評価規準の選択一致性と頑健性の両立について

    倉田澄人, 濵田悦生

    日本統計学会春季集会ポスターセッション  2019.3 

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    Event date: 2019.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:日本大学   Country:Japan  

  • 一般化尤度に基づいたモデル評価規準の性質について Invited

    倉田澄人, 濵田悦生

    RIMS共同研究「高次元量子雑音の統計モデリング」  2018.11 

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    Event date: 2018.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:京都大学   Country:Japan  

  • 意思決定問題へのダイバージェンスを用いた統計学的アプローチ

    倉田澄人, 濵田悦生

    統計関連学会連合大会  2018.9 

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    Event date: 2018.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:中央大学   Country:Japan  

  • ダイバージェンスに基づくモデル評価規準の一致性と頑健性について

    倉田澄人, 濵田悦生

    国際数理科学協会「統計的推測と統計ファイナンス」分科会研究集会  2018.8 

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    Event date: 2018.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:大阪大学   Country:Japan  

  • 社会調査データに対する確率的モデルと頑健な分析

    倉田澄人, 濵田悦生

    日本統計学会春季集会ポスターセッション  2018.3 

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    Event date: 2018.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:早稲田大学   Country:Japan  

  • AHP・ANPの一対比較行列に対する統計的解析手法の検討

    倉田澄人, 濵田悦生

    RIMS共同研究「不確実性の下での意思決定理論とその応用:計画数学の展開」  2017.11 

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    Event date: 2017.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:京都大学   Country:Japan  

  • 統計的因果推論と頑健なモデル選択について

    倉田澄人, 濵田悦生

    統計関連学会連合大会  2017.9 

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    Event date: 2017.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:南山大学   Country:Japan  

  • ロバスト性を持ったモデル評価規準族の応用について

    倉田澄人, 濵田悦生

    国際数理科学協会「統計的推測と統計ファイナンス」分科会研究集会  2017.8 

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    Event date: 2017.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:大阪府立大学   Country:Japan  

  • A robust model selection criterion family and its application for the causal model International conference

    Sumito Kurata, Etsuo Hamada

    International Federation of Classification Societies  2017.8 

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    Event date: 2017.8

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Tokai University   Country:Japan  

  • 異常値の混入した因果ダイアグラムの選択

    倉田澄人, 濵田悦生

    日本統計学会春季集会ポスターセッション  2017.3 

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    Event date: 2017.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:政策研究大学院大学   Country:Japan  

  • AICを含む規準族の漸近性質とロバスト性に関する研究報告 Invited

    倉田澄人, 濵田悦生

    九州大学IMIシンポジウム「高精度情報抽出のための統計理論・方法論とその応用」  2016.11 

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    Event date: 2016.11

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:九州大学   Country:Japan  

  • 頑健なダイバージェンスに基づいたモデル評価規準の統計的性質

    倉田澄人, 濵田悦生

    統計関連学会連合大会  2016.9 

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    Event date: 2016.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:金沢大学   Country:Japan  

  • 漸近的過剰・過小適合確率と規準のロバスト性について

    倉田澄人, 濵田悦生

    国際数理科学協会「統計的推測と統計ファイナンス」分科会研究集会  2016.8 

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    Event date: 2016.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:大阪大学   Country:Japan  

  • 回帰モデルの選択規準と外れ値に対するロバスト性の検証

    倉田澄人, 濵田悦生

    日本統計学会春季集会ポスターセッション  2016.3 

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    Event date: 2016.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:東北大学   Country:Japan  

  • ダイバージェンスを用いたロバスト推定とモデル選択規準について

    倉田澄人, 濵田悦生

    統計関連学会連合大会  2015.9 

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    Event date: 2015.9

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:岡山大学   Country:Japan  

  • BHHJ-divergenceに基づいたモデル評価規準の提案と考察

    倉田澄人, 濵田悦生

    国際数理科学協会「統計的推測と統計ファイナンス」分科会研究集会  2015.8 

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    Event date: 2015.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:大阪府立大学   Country:Japan  

  • 最小phi-divergence推定量を用いたロジスティック回帰問題

    倉田澄人, 熊谷悦生

    日本統計学会春季集会ポスターセッション  2015.3 

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    Event date: 2015.3

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:明治大学   Country:Japan  

  • 情報量規準と次数選択問題について

    倉田澄人, 熊谷悦生

    国際数理科学協会「統計的推測と統計ファイナンス」分科会研究集会  2014.8 

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    Event date: 2014.8

    Language:Japanese   Presentation type:Oral presentation (general)  

    Venue:関西学院大学   Country:Japan  

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MISC

  • Correction to: Statistical modeling for temporal dominance of sensations data incorporating individual characteristics of panelists: an application to data of milk chocolate (Journal of Food Science and Technology, (2022), 59, 6, (2420-2428), 10.1007/s13197-021-05260-9)

    Kurata S., Kuroda R., Komaki F.

    Journal of Food Science and Technology   59 ( 6 )   2022.6   ISSN:00221155

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    Publisher:Journal of Food Science and Technology  

    The article ‘‘Statistical modeling for temporal dominance of sensations data incorporating individual characteristics of panelists: an application to data of milk chocolate’’, written by Sumito Kurata, Reiko Kuroda and Fumiyasu Komaki was originally published electronically on the publisher’s internet portal on 24th September, 2021 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on 4th October, 2021 to © The Author(s) 2021 and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The original article has been updated.

    DOI: 10.1007/s13197-021-05311-1

    Scopus

Professional Memberships

  • The Japan Statistical Society

  • International Society for Mathematical Sciences

Academic Activities

  • Screening of academic papers

    Role(s): Peer review

    2024

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

  • Program and local organizing committee International contribution

    Forum "Math-for-Industry" 2023 -MfI2.0-  ( Kyushu University Nishijin Plaza (2-16-23 Nishijin, Sawara-ku, Fukuoka 814-0002, JAPAN) Japan ) 2023.8 - 2023.9

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    Type:Competition, symposium, etc. 

  • Screening of academic papers

    Role(s): Peer review

    2023

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

  • Screening of academic papers

    Role(s): Peer review

    2022

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

  • Screening of academic papers

    Role(s): Peer review

    2021

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:2

  • Screening of academic papers

    Role(s): Peer review

    2020

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    Type:Peer review 

    Number of peer-reviewed articles in foreign language journals:1

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Research Projects

  • 界面マルチスケール4次元解析による革新的接着技術の構築

    2023.4

    九州大学 

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    Authorship:Coinvestigator(s) 

  • Development of model evaluation criteria based on statistical divergence and evaluation for criteria

    Grant number:20K19753  2020 - 2023

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Early-Career Scientists

    Kurata Sumito

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    Authorship:Principal investigator  Grant type:Scientific research funding

    In real data, there frequently exist some outliers (observations that are markedly different in value from others) derived from, for example, unusual abilities, catastrophe-level phenomena, or human errors. It is difficult to provide a clear definition or threshold of such outliers, moreover, it is effectively impossible to prevent their occurrence, thus, robust methods that reduce the influence of outliers are significantly important. In this study, I investigated a model selection methods that are robust against outliers. By utilizing statistical divergence, a measure of remoteness between probability distributions, I measured the "farness" between the model and the underlying "true distribution", and derived a model that can adequately represent a phenomenon or behavior. Additionally, I theoretically evaluated the performance of the selection method.

    CiNii Research

  • 次世代地震計測と最先端ベイズ統計学との融合によるインテリジェント地震波動解析

    2019.2 - 2023.3

    東京大学 地震研究所(日本) 

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    Authorship:Coinvestigator(s) 

  • ダイバージェンスに基づいたモデル評価規準の提案と考案

    Grant number:16J04579  2016 - 2018

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for JSPS Fellows

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    Authorship:Principal investigator  Grant type:Scientific research funding

Educational Activities

  • マス・フォア・インダストリ研究所教員として、数理学府・理学部における教育活動を実施する。

    (以下、他の教育活動内容)
    東京大学:授業・演習担当 (2019/04-2022/09)
    東京大学エクステンション:社会人向けデータサイエンススクール講師担当 (2020/04-)

Class subject

  • 統計数学・演習

    2023.10 - 2024.3   Second semester

  • 情報統計学演習

    2023.10 - 2024.3   Second semester

  • 数理統計学

    2023.4 - 2023.9   First semester

  • 統計科学・演習

    2024.4 - 2024.9   First semester

  • 数理統計学

    2024.4 - 2024.9   First semester

Visiting, concurrent, or part-time lecturers at other universities, institutions, etc.

  • 2024  東京大学エクステンション(社会人向けデータサイエンススクール)  Classification:Part-time lecturer  Domestic/International Classification:Japan 

  • 2023  東京大学エクステンション(社会人向けデータサイエンススクール)  Classification:Part-time lecturer  Domestic/International Classification:Japan 

  • 2022  東京大学エクステンション(社会人向けデータサイエンススクール)  Classification:Part-time lecturer  Domestic/International Classification:Japan 

Other educational activity and Special note

  • 2023  Special Affairs  2023年12月14日(木)・15日(金)開催の、学外(産業界・行政機関・研究者・学生)向けの「産業数理統計チュートリアル」にて、「回帰の基礎、高次元線形回帰モデル」の講義を担当した。

     詳細を見る

    2023年12月14日(木)・15日(金)開催の、学外(産業界・行政機関・研究者・学生)向けの「産業数理統計チュートリアル」にて、「回帰の基礎、高次元線形回帰モデル」の講義を担当した。

Social Activities

  • 産業数理統計チュートリアル

    Role(s):Lecturer

    九州大学 マス・フォア・インダストリ研究所 産業数理統計研究部門  日時:2023年12月14日(木)・15日(金) 10:00~16:30会場:九州大学伊都キャンパス ウエスト1号館 C-408 大会議室  2023.12

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    Type:Lecture

    九州大学が推進する「脱炭素」「医療・健康」「環境・食料」の社会課題において、数理・データサイエンス・AIを学術的基盤とした研究のニーズが急速に高まっています。そこで、統計分野を中核とする分野横断数理基盤の形成を目指し、2022年4月にマス・フォア・インダストリ研究所(IMI)に産業数理統計研究部門が設置されました。産業数理統計研究部門では、統計学の学理を深めるとともに、社会や産業、諸分野の多様な課題の解決に貢献し、統計の若手中核の人材育成を行っています。とくに、データサイエンスや統計学を活用して産業や社会の課題解決に活躍できる次世代技術者の養成のため、チュートリアルを開催します。


    受講対象者
    業務でデータサイエンスや関連領域の知識や技術を必要とする産業界や行政機関の方々
    研究で統計学を必要とする研究者や大学院生・学部生

  • 日本官能評価学会企業部会第105回定例会における講演「マルコフ連鎖と一般化線形モデルによるTDSデータの分析について」

    Role(s):Lecturer, Informant

    日本官能評価学会企業部会  ハイブリッド開催(オンライン&キリンホールディングス飲料未来研究所)  2023.3

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    Type:Seminar, workshop

  • 東京大学エクステンション 講師 (2020/04~) 社会人向けの統計学・データサイエンススクール

    Role(s):Lecturer, Informant, Demonstrator

    東京大学エクステンション  オンライン  2020.4 - Present

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    Audience:General, Scientific, Company, Civic organization, Governmental agency

    Type:Other