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Shimizu Shohei  清水 昌平

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SHIMIZU Shohei  清水 昌平

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Researcher Number 10509871
Other IDs
Affiliation (Current) 2025: 大阪大学, 産業科学研究所, 教授
Affiliation (based on the past Project Information) *help 2022 – 2025: 滋賀大学, データサイエンス学系, 教授
2017 – 2021: 滋賀大学, データサイエンス学部, 教授
2016 – 2017: 滋賀大学, データサイエンス学部, 准教授
2016: 滋賀大学, データサイエンス教育研究センター, 准教授
2012 – 2015: 大阪大学, 産業科学研究所, 准教授
2009 – 2012: Osaka University, 産業科学研究所, 助教
Review Section/Research Field
Principal Investigator
Basic Section 60030:Statistical science-related / Statistical science / Sections That Are Subject to Joint Review: Basic Section60030:Statistical science-related , Basic Section61030:Intelligent informatics-related / Basic Section 61030:Intelligent informatics-related / Statistical science
Except Principal Investigator
Intelligent informatics / Intelligent informatics / Statistical science / Medium-sized Section 61:Human informatics and related fields / A New Phase of Our Advanced Science and Technology Society / Intensification of Artifact Systems / Statistical science
Keywords
Principal Investigator
因果探索 / 因果構造探索 / 統計的因果推論 / 因果推論 / 非ガウス性 / 構造方程式モデル / 統計的因果探索 / 個体レベル / 最適介入 / 制御 … More / 説明性 / 構造的因果モデル / 異質性 / 未観測共通原因 / 観察データ / 因果構造 / LiNGAM / 非ガウス / 因果方向推定 / 潜在共通原因 / 米国 / 国際情報交換 / 複数データセット / 機械学習 / 統計数学 / 独立成分分析 … More
Except Principal Investigator
データマイニング / 機械学習 / 高次元データ / 超高次元データ / 統計的推定 / 希少事象 / 知識発見 / 多変量解析 / リスク / 粒子フィルタ / 次元の呪い / ビッグデータ / 統計的因果推論 / 因果推論 / 因果構造 / ポイズニング / 敵対的サンプル / 深層学習 / データ / 診断 / ELSI / 医療機器 / 仮名化 / ELSI / AI / 人間の尊厳 / 医療データ / 同意 / 責任 / 個人情報保護 / 生命倫理 / AI / 情報デザイン / 老年医学 / 臨床疫学 / ヘルスデータ / 健康コミュニティ / ヘルスシステム / IoT / 高齢者 / 人工物システム / 介護予防 / 疫学 / シミュレーション / 人工知能 / 画像検索 / 漸近理論 / 自然言語処理 / マルチモーダル / ニューラルネットワーク / 分散表現 / 次元削減 / グラフ埋め込み / パターン認識 / 大規模データ / 列挙探索 / 心疾患モデル / アンサンブル学習 / アンサンブル / サンプリング / モデリング / 降雨確率モデル / 河川水流モデル / 大規模洪水 / 希少シナリオ / 確率的シミュレーション / マルコフチェインモンテカルロ / 希少事象シミュレーション / 希少事象解析 / 災害 / 確率モデル / 分子系統学 / マルチスケール / ベイズ統計 / ブートストラップ・リサンプリング / GPGPU / 統計的推測 / ダイバージェンス / クロスバリデーション / 高次漸近理論 / 情報幾何 / モデル選択 / 仮説検定 / スケーリング則 / リサンプリング / ブートストラップ / 強い意味で無視可能 / 推定方程式の不偏性 / ベイズ推測 / Approximate Population Bias / NMARness / 因果と欠測 / ランダムな欠測 / 交絡変数 / 補助変数 / 欠測値問題とMAR / 無視可能性 / 統計教育 / 人口データ解析 / 潜在変数モデル / 大量欠測 / 因果と予測 / 2重中途打ち切り / 潜在交絡変数 / LiNGAM / NMAR / 無視できない欠測 / shared-parameter モデル / データ分布 / 確率密度関数 / 統計数理 / 知能発見 / 高速相関係数推定 / 少数事例データ / 因果ネットワーク / 大規模変数次元データ / 遺伝子発現度測定データ / 独立成分分析 / 遺子機能 / グラフマイニング / 知識ベース / 遺伝子機能 / 大規模次元 Less
  • Research Projects

    (16 results)
  • Research Products

    (175 results)
  • Co-Researchers

    (42 People)
  •  デジタルツイン因果推論の研究とそれによる環境変化に頑健な機械学習実装の実現Principal Investigator

    • Principal Investigator
      清水 昌平
    • Project Period (FY)
      2025 – 2028
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 60030:Statistical science-related
      Basic Section 61030:Intelligent informatics-related
      Sections That Are Subject to Joint Review: Basic Section60030:Statistical science-related , Basic Section61030:Intelligent informatics-related
    • Research Institution
      Shiga University
  •  Understanding Attack Mechanisms against AI through Causal Structures of Classification and Building Countermeasures

    • Principal Investigator
      佐久間 淳
    • Project Period (FY)
      2023 – 2027
    • Research Category
      Grant-in-Aid for Scientific Research (A)
    • Review Section
      Medium-sized Section 61:Human informatics and related fields
    • Research Institution
      Institute of Science Tokyo
  •  未観測共通原因が存在する場合の巡回因果モデル推定法の研究と応用Principal Investigator

    • Principal Investigator
      清水 昌平
    • Project Period (FY)
      2020 – 2024
    • Research Category
      Grant-in-Aid for Scientific Research (C)
    • Review Section
      Basic Section 60030:Statistical science-related
    • Research Institution
      Shiga University
  •  Bioethics in AI - Overall Perspective and Direction for Future Researches in This Field

    • Principal Investigator
      位田 隆一
    • Project Period (FY)
      2020 – 2024
    • Research Category
      Grant-in-Aid for Challenging Research (Exploratory)
    • Review Section
      A New Phase of Our Advanced Science and Technology Society
    • Research Institution
      Shiga University
  •  Developing "happy aging community"by integrated health data

    • Principal Investigator
      Fukuma Shingo
    • Project Period (FY)
      2017 – 2019
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Intensification of Artifact Systems
    • Research Institution
      Kyoto University
  •  Multivariate analysis of multi-domain data considering the association between data vectors

    • Principal Investigator
      Shimodaira Hidetoshi
    • Project Period (FY)
      2016 – 2019
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Statistical science
    • Research Institution
      Kyoto University
      Osaka University
  •  Causal discovery in the presence of hidden confounding variables for data with heterogeneityPrincipal Investigator

    • Principal Investigator
      Shimizu Shohei
    • Project Period (FY)
      2016 – 2019
    • Research Category
      Grant-in-Aid for Scientific Research (C)
    • Research Field
      Statistical science
    • Research Institution
      Shiga University
  •  Model Mining: Exploration of search and enumeration methods of local models from super-high dimensional data

    • Principal Investigator
      Washio Takashi
    • Project Period (FY)
      2014 – 2015
    • Research Category
      Grant-in-Aid for Challenging Exploratory Research
    • Research Field
      Intelligent informatics
    • Research Institution
      Osaka University
  •  Development and Application of Statistical Estimation and Simulation for Super High Dimensional Data Space

    • Principal Investigator
      Washio Takashi
    • Project Period (FY)
      2013 – 2016
    • Research Category
      Grant-in-Aid for Scientific Research (A)
    • Research Field
      Intelligent informatics
    • Research Institution
      Osaka University
  •  Computing confidence levels of many hypotheses for high-dimensional data

    • Principal Investigator
      Shimodaira Hidetoshi
    • Project Period (FY)
      2012 – 2015
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Statistical science
    • Research Institution
      Osaka University
  •  Learning Probabilistic Simulation Models for Rare Event/Condition Occurrence

    • Principal Investigator
      WASHIO Takashi
    • Project Period (FY)
      2012 – 2013
    • Research Category
      Grant-in-Aid for Challenging Exploratory Research
    • Research Field
      Intelligent informatics
    • Research Institution
      Osaka University
  •  Estimation of high-dimensional causal networks based on multiple datasets and its applications to biomedical sciencePrincipal Investigator

    • Principal Investigator
      Shimizu Shohei
    • Project Period (FY)
      2012 – 2015
    • Research Category
      Grant-in-Aid for Young Scientists (B)
    • Research Field
      Statistical science
    • Research Institution
      Osaka University
  •  Establishment of Statistical Estimation Principle for Super HighDimensional Data and Its Application to Large Scale Data Mining

    • Principal Investigator
      WASHIO Takashi
    • Project Period (FY)
      2010 – 2012
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Intelligent informatics
    • Research Institution
      Osaka University
  •  Statistical prediction, causation, incomplete data analysis and foundation of sciencee

    • Principal Investigator
      KANO YUTAKA
    • Project Period (FY)
      2010 – 2013
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Statistical science
    • Research Institution
      Osaka University
  •  Discovery of reliable causal structures in high-dimensional dataPrincipal Investigator

    • Principal Investigator
      SHIMIZU Shohei
    • Project Period (FY)
      2009 – 2011
    • Research Category
      Grant-in-Aid for Young Scientists (B)
    • Research Field
      Statistical science
    • Research Institution
      Osaka University
  •  Development of Causal Structure Mining Method for Large Scale Dimensional Data and Construction of Gene Function Knowledge Base

    • Principal Investigator
      WASHIO Takashi
    • Project Period (FY)
      2007 – 2009
    • Research Category
      Grant-in-Aid for Scientific Research (A)
    • Research Field
      Intelligent informatics
    • Research Institution
      Osaka University

All 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 Other

All Journal Article Presentation Book

  • [Book] Statistical Causal Discovery: LiNGAM Approach2022

    • Author(s)
      Shohei Shimizu
    • Total Pages
      94
    • Publisher
      Springer, Tokyo
    • ISBN
      9784431557845
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Book] 統計的因果探索2017

    • Author(s)
      清水 昌平
    • Total Pages
      192
    • Publisher
      講談社
    • ISBN
      9784061529250
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Book] 確率的グラフィ カルモデル2016

    • Author(s)
      黒木学, 清水昌平, 湊真一, 石畠正和, 樺島祥介, 田中和之, 本村陽一, 玉田嘉紀, 鈴木譲, 植野真臣
    • Total Pages
      292
    • Publisher
      共立出版
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Book] Consistency of penalized risk of boosting methods in binary classification, In New Trends in Psychometrics, Post Proceedings of IMPS2007: the 15th International and 72nd Annual Meeting of the Psychometric Society2009

    • Author(s)
      K. Hayashi, Y. Shimizu, Y. Kano
    • Publisher
      Psychometric Society (in press)
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Journal Article] Structure Learning for Groups of Variables in Nonlinear Time-Series Data with Location-Scale Noise2023

    • Author(s)
      Genta Kikuchi, Shohei Shimizu
    • Journal Title

      Proc. Causal Analysis Workshop 2023 (CAWS2023), PMLR

      Volume: 223 Pages: 20-39

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Linkages among the Foreign Exchange, Stock, and Bond Markets in Japan and the United States2023

    • Author(s)
      Yi Jiang, Shohei Shimizu
    • Journal Title

      Proceedings of the 2023 Causal Analysis Workshop Series, PMLR

      Volume: 223 Pages: 1-19

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Python package for causal discovery based on LiNGAM 著者2023

    • Author(s)
      Takashi Ikeuchi, Mayumi Ide, Yan Zeng, Takashi Nicholas Maeda, Shohei Shimizu
    • Journal Title

      Journal of Machine Learning Research

      Volume: 24 Pages: 1-8

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Causal Discovery for Linear Mixed Data2022

    • Author(s)
      Yan Zeng, Shohei Shimizu, Hidetoshi Matsui, Fuchun Sun
    • Journal Title

      Proceedings of the First Conference on Causal Learning and Reasoning, PMLR

      Volume: 177 Pages: 994-1009

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Chemical-Mediated Microbial Interactions Can Reduce the Effectiveness of Time-Series-Based Inference of Ecological Interaction Networks2022

    • Author(s)
      Suzuki Kenta、Abe Masato S.、Kumakura Daiki、Nakaoka Shinji、Fujiwara Fuki、Miyamoto Hirokuni、Nakaguma Teruno、Okada Mashiro、Sakurai Kengo、Shimizu Shohei、Iwata Hiroyoshi、Masuya Hiroshi、Nihei Naoto、Ichihashi Yasunori
    • Journal Title

      International Journal of Environmental Research and Public Health

      Volume: 19 Issue: 3 Pages: 1228-1228

    • DOI

      10.3390/ijerph19031228

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K06820, KAKENHI-PROJECT-20K11708, KAKENHI-PROJECT-21K19813
  • [Journal Article] CNN-GRU Based Deep Learning Model for Demand Forecast in Retail Industry2022

    • Author(s)
      Kazuhi Honjo, Xiaokang Zhou, Shohei Shimizu
    • Journal Title

      Proc. 2022 International Joint Conference on Neural Networks (IJCNN)

      Volume: - Pages: 1-8

    • DOI

      10.1109/ijcnn55064.2022.9892599

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Estimating individual-level optimal causal interventions combining causal models and machine learning models2021

    • Author(s)
      Keisuke Kiritoshi, Tomonori Izumitani, Kazuki Koyama, Tomomi Okawachi, Keisuke Asahara, Shohei Shimizu
    • Journal Title

      Proceedings of The KDD'21 Workshop on Causal Discovery, PMLR

      Volume: 150 Pages: 55-77

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Causal Discovery with Multi-Domain LiNGAM for Latent Factors2021

    • Author(s)
      Zeng Yan、Shimizu Shohei、Cai Ruichu、Xie Feng、Yamamoto Michio、Hao Zhifeng
    • Journal Title

      Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence

      Volume: - Pages: 2097-2103

    • DOI

      10.24963/ijcai.2021/289

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17K12648, KAKENHI-PROJECT-20K11708
  • [Journal Article] Causal additive models with unobserved variables2021

    • Author(s)
      Takashi Nicholas Maeda, Shohei Shimizu
    • Journal Title

      Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, PMLR

      Volume: 161 Pages: 97-106

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Nonlinear Causal Discovery for High-Dimensional Deterministic Data2021

    • Author(s)
      Zeng Yan、Hao Zhifeng、Cai Ruichu、Xie Feng、Huang Libo、Shimizu Shohei
    • Journal Title

      IEEE Transactions on Neural Networks and Learning Systems

      Volume: - Issue: 5 Pages: 1-12

    • DOI

      10.1109/tnnls.2021.3106111

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders2020

    • Author(s)
      T. N. Maeda, S Shimizu
    • Journal Title

      Proc. 23rd International Conference on Artificial Intelligence and Statistics (AISTATS2020)

      Volume: 1 Pages: 1-9

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders2020

    • Author(s)
      Takashi Nicholas Maeda, Shohei Shimizu
    • Journal Title

      Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics

      Volume: 108 Pages: 735-745

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Journal Article] Personalization Recommendation Algorithm Based on Trust Correlation Degree and Matrix Factorization2019

    • Author(s)
      Li Weimin、Zhou Xiaokang、Shimizu Shohei、Xin Mingjun、Jiang Jiulei、Gao Honghao、Jin Qun
    • Journal Title

      IEEE Access

      Volume: 7 Pages: 45451-45459

    • DOI

      10.1109/access.2018.2885084

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] Multi-Modality Behavioral Influence Analysis for Personalized Recommendations in Health Social Media Environment2019

    • Author(s)
      Zhou Xiaokang、Liang Wei、Wang Kevin I-Kai、Shimizu Shohei
    • Journal Title

      IEEE Transactions on Computational Social Systems

      Volume: 6 Issue: 5 Pages: 888-897

    • DOI

      10.1109/tcss.2019.2918285

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] Analysis of cause-effect inference by comparing regression errors2019

    • Author(s)
      Blobaum Patrick、Janzing Dominik、Washio Takashi、Shimizu Shohei、Scholkopf Bernhard
    • Journal Title

      PeerJ Computer Science

      Volume: 5 Pages: e169-e169

    • DOI

      10.7717/peerj-cs.169

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045, KAKENHI-PROJECT-17K00305, KAKENHI-PROJECT-15H05711
  • [Journal Article] Cause-Effect Inference by Comparing Regression Errors2018

    • Author(s)
      Patrick Bloebaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schoelkopf
    • Journal Title

      Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS2018), PMLR

      Volume: 84 Pages: 900-909

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] Non-Gaussian Methods for Causal Structure Learning2018

    • Author(s)
      Shimizu Shohei
    • Journal Title

      Prevention Science

      Volume: 20 Issue: 3 Pages: 431-441

    • DOI

      10.1007/s11121-018-0901-x

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-16K00045, KAKENHI-PROJECT-16H02789
  • [Journal Article] A novel principle for causal inference in data with small error variance2018

    • Author(s)
      Patrick Bloebaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, Bernhard Schoelkopf
    • Journal Title

      Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, PMLR

      Volume: 84 Pages: 900-909

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-16H02789
  • [Journal Article] A Novel Personalized Recommendation Algorithm Based on Trust Relevancy Degree2018

    • Author(s)
      Li Weimin、Zhu Heng、Zhou Xiaokang、Shimizu Shohei、Xin Mingjun、Jin Qun
    • Journal Title

      Proc. DASC/PiCom/DataCom/CyberSciTec2018

      Volume: 1 Pages: 418-422

    • DOI

      10.1109/dasc/picom/datacom/cyberscitec.2018.00084

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] A novel principle for causal inference in data with small error variance2017

    • Author(s)
      Blobaum Patrick、Shimizu Shohei、Washio Takashi
    • Journal Title

      n Proc. 25 th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN2017),

      Volume: 1 Pages: 347-352

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] Learning instrumental variables with structural and non-Gaussianity assumptions2017

    • Author(s)
      Ricard Silva, Shohei Shimizu
    • Journal Title

      Journal of Machine Learning Research

      Volume: 18 Pages: 1-49

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] Error asymmetry in causal and anticausal regression2017

    • Author(s)
      Blobaum Patrick、Washio Takashi、Shimizu Shohei
    • Journal Title

      Behaviormetrika

      Volume: 44 Issue: 2 Pages: 491-512

    • DOI

      10.1007/s41237-017-0022-z

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045, KAKENHI-PROJECT-17K00305, KAKENHI-PROJECT-15H05711
  • [Journal Article] Estimation of interventional effects of features on prediction2017

    • Author(s)
      Blobaum Patrick、Shimizu Shohei
    • Journal Title

      Proc. 2017 IEEE Machine Learning for Signal Processing Workshop (MLSP2017)

      Volume: 1 Pages: 1-6

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] Non-Gaussian structural equation models for causal discovery2016

    • Author(s)
      S. Shimizu
    • Journal Title

      Statistics and Causality: Methods for Applied Empirical Research

      Volume: - Pages: 153-184

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Journal Article] Discriminative and Generative Models in Causal and Anticausal Settings2015

    • Author(s)
      Patrick Blobaum, Shohei Shimizu, Takashi Washio
    • Journal Title

      Advanced Methodologies for Bayesian Networks, Lecture Notes in Computer Science

      Volume: 9505 Pages: 209-221

    • DOI

      10.1007/978-3-319-28379-1_15

    • ISBN
      9783319283784, 9783319283791
    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-24700275, KAKENHI-PROJECT-24300106
  • [Journal Article] A non-Gaussian approach for causal discovery in the presence of hidden common causes2015

    • Author(s)
      Shohei Shimizu
    • Journal Title

      Advanced Methodologies for Bayesian Networks, Lecture Notes in Computer Science

      Volume: 9505 Pages: 222-223

    • DOI

      10.1007/978-3-319-28379-1_16

    • ISBN
      9783319283784, 9783319283791
    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-24700275, KAKENHI-PROJECT-24300106
  • [Journal Article] ParceLiNGAM : A causal ordering method robust against latent confounders2014

    • Author(s)
      Tashiro, T., Shimizu, S., Hyvarinen, A. and Washio, T
    • Journal Title

      Neural Computation

      Volume: 26(1) Issue: 1 Pages: 57-83

    • DOI

      10.1162/neco_a_00533

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-22300096, KAKENHI-PROJECT-24300106, KAKENHI-PROJECT-24700275, KAKENHI-PROJECT-25240036
  • [Journal Article] Bayesian estimation of causal direction in acyclic structural equation models with individual-specific confounder variables and non-Gaussian distributions2014

    • Author(s)
      S. Shimizu and K. Bollen
    • Journal Title

      Journal of Machine LearningResearch

      Volume: 15 Pages: 2629-2652

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Journal Article] Bayesian estimation of causal direction in acyclic structural equation models with individual-specific confounder variables and non-Gaussian distributions2014

    • Author(s)
      Shohei Shimizu and Kenneth Bollen
    • Journal Title

      Journal of Machine Learning Research

      Volume: 15 Pages: 2629-2652

    • Peer Reviewed / Acknowledgement Compliant / Open Access
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Journal Article] Joint estimation of linear non-Gaussian acyclic models2012

    • Author(s)
      S. Shimizu
    • Journal Title

      Neurocomputing

      Volume: 81 Pages: 104-107

    • DOI

      10.1016/j.neucom.2011.11.005

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302, KAKENHI-PROJECT-24300106, KAKENHI-PROJECT-24700275
  • [Journal Article] Analyzing relationships among ARMA processes based on non-Gaussianity of external influences2011

    • Author(s)
      Y. Kawahara, S. Shimizu, and T. Washio
    • Journal Title

      eurocomputing

      Volume: 74(12-13) Pages: 2212-2221

    • URL

      http://dx.doi.org/10.1016/j.neucom.2011.02.008

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Journal Article] Analyzing relationships among ARMA processes based on non-Gaussianity of external influences2011

    • Author(s)
      Yoshinobu Kawahara, Shohei Shimizu, Takashi Washio
    • Journal Title

      Neurocomputing

      Volume: Vol.74,No.12-13 Pages: 2212-2221

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Journal Article] DirectLiNGAM : A direct method for learning a linear non-Gaussian structural equation model2011

    • Author(s)
      S.Shimizu, T.Inazumi, Y.Sogawa, A.Hyvarinen, Y.Kawahara, T.Washio, P.O.Hoyer, K.Bollen
    • Journal Title

      Journal of Machine Learning Research

      Volume: 12 Pages: 1225-1248

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Journal Article] Analyzing Relationships among ARMA Processes Based on Non-Gaussianity of External Influences2011

    • Author(s)
      Yoshinobu Kawahara, Shohei Shimizu, Takashi Washio
    • Journal Title

      Neurocomputing

      Volume: (Accepted)

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Journal Article] Estimating exogenous variables in data with more variables than observations2011

    • Author(s)
      Y.Sogawa, S.Shimizu, T.Shimamura, A.Hyvarinen, T.Washio and S.Imoto
    • Journal Title

      Neural Networks

      Volume: 24(8) Pages: 875-880

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Journal Article] DirectLiNGAM : A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model2011

    • Author(s)
      Shohei Shimizu, Takanori Inazumi, Yasuhiro Sogawa, Aapo Hyvarinen, Yoshinobu Kawahara, Takashi Washio, Patrik O.Hoyer, Kenneth Bollen
    • Journal Title

      Journal of Machine Learning Research

      Volume: Vol.12 Pages: 1225-1248

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Journal Article] Analyzing relationships among ARMA processes based on non-Gaussianity of external influences2011

    • Author(s)
      Y.Kawahara, S.Shimizu, T.Washio
    • Journal Title

      Neurocomputing

      Volume: 74 Issue: 12-13 Pages: 2212-2221

    • DOI

      10.1016/j.neucom.2011.02.008

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302, KAKENHI-PROJECT-22700147
  • [Journal Article] DirectLiNGAM : A direct method for learning a linear non-Gaussian structural equation model2011

    • Author(s)
      S. Shimizu, T. Inazumi, Y. Sogawa, A. Hyvarinen, Y. Kawahara, T. Washio, P. O. Hoyer, and K. Bollen.
    • Journal Title

      Journal of Machine Learning Research

      Pages: 1225-1248

    • URL

      http://jmlr.csail.mit.edu/papers/volume12/shimizu11a/shimizu11a.pdf

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Journal Article] Estimating exogenous variables in data with more variables than observations2011

    • Author(s)
      Y. Sogawa, S. Shimizu, T. Shimamura, A. Hyvarinen, T. Washio, and S. Imoto
    • Journal Title

      Neural Networks

      Volume: 24(8) Issue: 8 Pages: 875-880

    • DOI

      10.1016/j.neunet.2011.05.017

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302, KAKENHI-PROJECT-22300054
  • [Journal Article] Estimation of a structural vector autoregression model using non-Gaussianity2010

    • Author(s)
      A.Hyvarinen, K.Zhang, S.Shimizu, P.O.Hoyer
    • Journal Title

      Journal of Machine Leanring Research

      Volume: 11 Pages: 1709-1731

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Journal Article] Estimation of a structural vector autoregression model using non-Gaussianity2010

    • Author(s)
      A. Hyvarinen, K. Zhang, S. Shimizu and P. O. Hoyer
    • Journal Title

      Journal of Machine Learning Research

      Pages: 1709-1731

    • URL

      http://jmlr.csail.mit.edu/papers/volume11/hyvarinen10a/hyvarinen10a.pdf

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Journal Article] A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model2009

    • Author(s)
      S.Shimizu, A.Hyvarinen, Y.Kawahata, T.Washio
    • Journal Title

      Proceedings of the Twenty-Fifth Conference Conference on Uncertainty in Artificial Intelligence

      Pages: 506-513

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Journal Article] Estimation of linear non-Gaussian acyclic models for latent factors2009

    • Author(s)
      S. Shimizu, P.O. Hoyer, A. Hyvarinen
    • Journal Title

      Neurocomputing Vol.72

      Pages: 2024-2027

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Journal Article] A direct method for estimating a causal ordering in a linear non-Gaussi an acyclic model2009

    • Author(s)
      Shohei Shimizu, Aapo Hyvarinen, Yoshinobu Kawahara, Takashi Washio
    • Journal Title

      Proc.Of UAI2009 : The 25th Conference on Uncetainty in Artificial Intelligence, Causality II & Graphical Models 1

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Journal Article] Use of Non-Normality in Structural Equation Modeling: Application to Direction of Causation2008

    • Author(s)
      S. Shimizu, Y. Kano
    • Journal Title

      J. of Statistical Planning and Inference Vol.138

      Pages: 3483-3491

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] 大規模言語モデルを活用した博士課程進学に関する因果探索の試行2023

    • Author(s)
      高山正行, 小柴等, 前田高志ニコラス, 三内顕義, 清水昌平
    • Organizer
      研究・イノベーション学会 第38回年次学術大会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 大学別の博士課程進学等に関するデータセットの構築と統計的因果探索2023

    • Author(s)
      高山正行, 小松尚登, ファムテトン, 前田高志ニコラス, 三内顕義, 小柴等, 清水昌平
    • Organizer
      研究・イノベーション学会 第38回年次学術大会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] Non-Gaussian methods for causal discovery2023

    • Author(s)
      Shohei Shimizu
    • Organizer
      16th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2023), Berlin. Organized Invited Session: Statistical Learning of Non-Gaussian Data
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 統計的因果探索アルゴリズム”LiNGAM”を用いた若手研究者支援政策に関する研究2022

    • Author(s)
      高山正行, 小柴等, 前田高志ニコラス, 三内顕義, 清水昌平, 星野利彦
    • Organizer
      研究・イノベーション学会 第37回年次学術大会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 時系列データに対する予測モデルの介入効果の推定2022

    • Author(s)
      藤原大悟, 小山和輝, 大川内智海, 泉谷知範, 浅原啓輔, 清水昌平
    • Organizer
      第36回人工知能学会全国大会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 統計的因果探索: 領域知識とデータによる因果構造グラフの推測2022

    • Author(s)
      清水昌平
    • Organizer
      第18回愛媛大学DS研究セミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 統計的因果探索とAI2022

    • Author(s)
      清水昌平
    • Organizer
      脳病態数理・データ科学セミナーシリーズ
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] セミパラメトリックアプローチによる統計的因果探索2021

    • Author(s)
      清水昌平
    • Organizer
      人工知能学会 第118回 人工知能基本問題研究会 (SIG-FPAI)
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] Causal Discovery with Multi-Domain LiNGAM for Latent Factors2021

    • Author(s)
      Y. Zeng, S. Shimizu, R. Cai, F. Xie, M. Yamamoto, Z. Hao
    • Organizer
      Causal Analysis Workshop Series 2021 (CAWS2021)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 統計的因果探索: セミパラメトリックアプローチを中心に2021

    • Author(s)
      清水昌平
    • Organizer
      電子情報通信学会 パターン認識・メディア理解(PRMU)研究会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] EBPMと統計的因果探索・数理モデルの利活用2021

    • Author(s)
      高山正行, 小柴等, 前田高志ニコラス, 三内顕義, 清水昌平, 星野利彦
    • Organizer
      研究・イノベーション学会 第36回年次学術大会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] LiNGAM approach to causal discovery2021

    • Author(s)
      S. Shimizu
    • Organizer
      The KDD2021 Workshop on Causal Discovery (CD2021)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 統計的因果探索アルゴリズム”LiNGAM” を用いた若手研究者支援政策に関する研究2021

    • Author(s)
      高山正行, 小柴等, 前田高志ニコラス, 三内顕義, 清水昌平, 星野利彦
    • Organizer
      研究・イノベーション学会 第36回年次学術大会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] プラントシミュレータを用いた時系列因果探索手法の評価2021

    • Author(s)
      小山和輝, 藤原大悟, 切通恵介, 大川内智海, 泉谷知範, 浅原啓輔, 清水昌平
    • Organizer
      電子情報通信学会 パターン認識・メディア理解(PRMU)研究会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] Statistical Estimation of Gene Regulatory Network2020

    • Author(s)
      Y. Imoto, Y. Hiraoka, S. Shimizu, T. Nicolas Maeda, Y. Kojima, M. Saitou
    • Organizer
      JSPS Core-to-Core Program “Establishing International Research Network of Mathematical Oncology”
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] Linear non-Gaussian models with latent variables for causal discovery2020

    • Author(s)
      Shohei Shimizu
    • Organizer
      The 2020 Pacific Causal Inference Conference
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] データ駆動による因果仮説探2020

    • Author(s)
      清水昌平
    • Organizer
      JST 研究開発戦略センター(CRDS)俯瞰セミナーシリーズ「機械学習と科学」
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 因果探索という道具2020

    • Author(s)
      清水昌平
    • Organizer
      一般社団法人データサイエンティスト協会 7thシンポジウム
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] Linear non-Gaussian models with latent variables for causal discovery2020

    • Author(s)
      Shohei Shimizu
    • Organizer
      The 2020 NeurIPS Workshop on Causal Discovery and Causality-Inspired Machine Learning
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] 時系列データに対する予測モデルの介入効果の推定2020

    • Author(s)
      切通恵介, 紅林亘, 泉谷知範, 小山和輝, 木村大地, 大川内智海, 清水昌平
    • Organizer
      第34回人工知能学会全国大会
    • Data Source
      KAKENHI-PROJECT-20K11708
  • [Presentation] Causal discovery based on non-Gaussianity of data and its applications2019

    • Author(s)
      Shohei SHIMIZU
    • Organizer
      日本行動計量学会 第47回大会
    • Invited
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] 統計的因果探索に基づく遺伝子制御ネットワークの推定2019

    • Author(s)
      井元佑介, 平岡裕章,清水昌平,前田高志ニコラス,小島洋児,斎藤通紀
    • Organizer
      応用数学合同研究集会2019
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] Causal discovery, prediction, and control2018

    • Author(s)
      S. Shimizu
    • Organizer
      Causal Modeling and Machine Learning (CaMaL) Workshop
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16H02789
  • [Presentation] 因果探索、予測、そして制御2018

    • Author(s)
      清水昌平
    • Organizer
      応用統計学会
    • Data Source
      KAKENHI-PROJECT-16H02789
  • [Presentation] 因果探索、予測、そして制御2018

    • Author(s)
      清水昌平
    • Organizer
      2018年度 統計関連学会連合大会, 東京. 応用統計学会企画セッション: 「統計的因果推論―基本的なアイデアから最近の発展まで―」
    • Invited
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] Causal discovery, prediction, and control2018

    • Author(s)
      Shohei Shimizu
    • Organizer
      Causal Modeling and Machine Learning (CaMaL) Workshop, Guangzhou, China.
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] Causal discovery, prediction mechanisms, and control2018

    • Author(s)
      S. Shimizu
    • Organizer
      The 5th meeting of the Institute of Mathematical Statistics (IMS) meeting series, the IMS Asia Pacific Rim Meeting (IMS-APRM)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16H02789
  • [Presentation] Causal discovery, prediction mechanisms, and control2018

    • Author(s)
      Shohei Shimizu
    • Organizer
      he 5th meeting of the Institute of Mathematical Statistics (IMS) meeting series, the IMS Asia Pacific Rim Meeting (IMS-APRM), Singapore
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] 因果探索入門2017

    • Author(s)
      清水 昌平
    • Organizer
      日本行動計量学会 第20回春の合宿セミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] 統計的因果推論への招待 - 因果構造探索を中心に -2017

    • Author(s)
      清水 昌平
    • Organizer
      システム制御情報学会・計測自動制御学会 チュートリアル講座2017
    • Invited
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] Causal discovery and prediction mechanisms2017

    • Author(s)
      Shohei Shimizu
    • Organizer
      France/Japan Machine Learning Workshop
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] 因果構造探索の基本2017

    • Author(s)
      清水昌平
    • Organizer
      研究集会: 因果推論の基礎
    • Place of Presentation
      統計数理研究所 (東京)
    • Year and Date
      2017-02-17
    • Invited
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] 因果探索への招待2017

    • Author(s)
      清水 昌平
    • Organizer
      電子情報通信学会IA(インターネットアーキテクチャ)/IN(情報ネットワーク)併催研究会
    • Invited
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] A non-Gaussian model for causal discovery in the presence of hidden common causes2016

    • Author(s)
      Shimizu, Shohei
    • Organizer
      Munich Workshop on Causal Inference and Information Theory
    • Place of Presentation
      Munich (Germany)
    • Year and Date
      2016-05-23
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16H02789
  • [Presentation] 因果探索と非ガウス性2016

    • Author(s)
      清水昌平
    • Organizer
      第11回協定講座シンポジウム: 計算科学とビジュアル・アナリティクス
    • Place of Presentation
      神戸大学 (兵庫県)
    • Year and Date
      2016-03-06
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 因果探索: 基本から最近の発展までを概説2016

    • Author(s)
      清水昌平
    • Organizer
      第23回情報論的学習理論と機械学習研究会 (IBISML)
    • Place of Presentation
      統計数理研究所 (東京都)
    • Year and Date
      2016-03-17
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] Non-Gaussian structural equation models for causal discovery2016

    • Author(s)
      Shohei Shimizu
    • Organizer
      2016 Probabilistic Graphical Model Workshop: Sparsity, Structure and High-dimensionality
    • Place of Presentation
      統計数理研究所 (東京都)
    • Year and Date
      2016-03-23
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] A non-Gaussian approach for causal structure learning in the presence of hidden common causes2016

    • Author(s)
      Shimizu, Shohei
    • Organizer
      CRM Workshop: Statistical Causal Inference and its Applications to Genetics
    • Place of Presentation
      Montreal (Canada)
    • Year and Date
      2016-07-25
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16H02789
  • [Presentation] Non-Gaussian structural equation models for causal discovery2016

    • Author(s)
      Shohei Shimizu
    • Organizer
      2016 Probabilistic Graphical Model Workshop: Sparsity, Structure and High-dimensionality
    • Place of Presentation
      統計数理研究所(東京都・立川市)
    • Year and Date
      2016-03-23
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] 因果探索: 観察データから因果仮説を探索する2016

    • Author(s)
      清水昌平
    • Organizer
      日本社会心理学会: 第3回春の方法論セミナー
    • Place of Presentation
      上智大学 (東京都)
    • Year and Date
      2016-03-16
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] A non-Gaussian approach for causal structure learning in the presence of hidden common causes2016

    • Author(s)
      S. Shimizu
    • Organizer
      CRM Workshop: Statistical Causal Inference and its Applications to Genetics
    • Place of Presentation
      Montreal (Canada)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] Statistical estimation of causal directions based on observational data2016

    • Author(s)
      Shohei Shimizu
    • Organizer
      The 3rd CiNet Conference - Neural Mechanism of Decision Making: Achievements and New Directions
    • Place of Presentation
      大阪大学 (大阪府)
    • Year and Date
      2016-02-05
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] A non-Gaussian model for causal discovery in the presence of hidden common causes2016

    • Author(s)
      S. Shimizu
    • Organizer
      A non-Gaussian model for causal discovery in the presence of hidden common causes
    • Place of Presentation
      Munich (Germany)
    • Year and Date
      2016-05-23
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] Non-Gaussian methods for causal discove2016

    • Author(s)
      Shohei Shimizu
    • Organizer
      International Workshop on Causal Inference
    • Place of Presentation
      統計数理研究所 (東京都)
    • Year and Date
      2016-01-07
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 関係流動性と消費者自民族中心主義の因果構造分析~非ガウス性を使った因果推論2016

    • Author(s)
      芳賀麻誉美, 清水昌平
    • Organizer
      日本マーケティング・サイエンス学会 第100回研究大会
    • Place of Presentation
      ホテル阪急エキスポパーク+大阪大学中之島センター (大阪)
    • Year and Date
      2016-12-27
    • Data Source
      KAKENHI-PROJECT-16K00045
  • [Presentation] Non-Gaussian methods for causal discovery2016

    • Author(s)
      Shohei Shimizu
    • Organizer
      International Workshop on Causal Inference
    • Place of Presentation
      統計数理研究所(東京都・立川市)
    • Year and Date
      2016-01-07
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] A non-Gaussian approach for causal discovery in the presence of hidden common causes2015

    • Author(s)
      Shohei Shimizu
    • Organizer
      Second Workshop on Advanced Methodologies for Bayesian Networks (AMBN2015)
    • Place of Presentation
      慶應義塾大学 (神奈川県)
    • Year and Date
      2015-11-17
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 非ガウス性を利用した因果構造探索2015

    • Author(s)
      清水昌平
    • Organizer
      2015年日本生態学会関東地区会シンポジウム「非ガウス性/非線形性/非対称性からの因果推論手法:その使いどころ・原理・実装を学ぶ」
    • Place of Presentation
      東京大学 (東京都)
    • Year and Date
      2015-08-06
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 構造方程式モデルによる因果探索と非ガウス性2015

    • Author(s)
      清水昌平
    • Organizer
      数学協働プログラム(数学・数理科学と諸科学・産業との協働によるイノベーション創出のための研究促進プログラム) ワークショップ: 確率的グラフィカルモデル
    • Place of Presentation
      電気通信大学, 東京
    • Year and Date
      2015-03-20
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 因果探索: データから因果の方向性等を調べる2015

    • Author(s)
      清水昌平
    • Organizer
      日本行動計量学会 第43回大会
    • Place of Presentation
      首都大学東京 (東京都)
    • Year and Date
      2015-09-02
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] A non-Gaussian approach for estimating possible causal direction in the presence of latent confounders2014

    • Author(s)
      S. Shimizu
    • Organizer
      Conference on Statistics and Causality 2014
    • Place of Presentation
      Vienna, Austria
    • Year and Date
      2014-05-23
    • Invited
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] Estimation of causal direction in the presence of latent confounders and linear non-Gaussian structural equation models2014

    • Author(s)
      S. Shimizu
    • Organizer
      Causal Modeling and Machine Learning (Post-ICML workshop)
    • Place of Presentation
      Beijing, China
    • Year and Date
      2014-06-25
    • Invited
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] 潜在クラスが存在する場合のベイズ的アプローチによる非ガウス因果構造推定法2014

    • Author(s)
      田中 直樹, 清水昌平, 鷲尾 隆
    • Organizer
      第28回人工知能学会全国大会
    • Place of Presentation
      ひめぎんホール, 愛媛
    • Year and Date
      2014-05-13
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] A performance comparison of generative and discriminative models in causal and anticausal problems2014

    • Author(s)
      Patrick Blobaum, Shohei Shimizu, and Takashi Washio
    • Organizer
      Seventeenth International Conference on Artificial Intelligence and Statistics
    • Place of Presentation
      レイキャビック(アイスランド)
    • Year and Date
      2014-04-22
    • Data Source
      KAKENHI-PROJECT-26540116
  • [Presentation] Estimation of causal direction in the presence of latent confounders and linear non-Gaussian structural equation models2014

    • Author(s)
      Shohei Shimizu
    • Organizer
      Causal Modeling and Machine Learning (Post-ICML workshop)
    • Place of Presentation
      Beijing, China
    • Year and Date
      2014-06-25
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] A performance comparison of generative and discriminative models in causal and anticausal problems2014

    • Author(s)
      Blobaum P., Shimizu S., and Washio T.
    • Organizer
      Seventeenth International Conference on Artificial Intelligence and Statistics
    • Place of Presentation
      レイキャビック(アイスランド)
    • Year and Date
      2014-04-22
    • Data Source
      KAKENHI-PROJECT-25240036
  • [Presentation] A non-Gaussian approach for estimating possible causal direction in the presence of latent confounders2014

    • Author(s)
      Shohei Shimizu
    • Organizer
      Conference on Statistics and Causality 2014
    • Place of Presentation
      Vienna, Austria
    • Year and Date
      2014-05-23
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] Estimation of Causal Structures in Longtudinal Data Using Non-Gaussianity2013

    • Author(s)
      Kento Kadowaki, Shohei Shimizu and Takashi Washio
    • Organizer
      Proc. of 2013 IEEE International Workshop on Machine Learning for Signal Processing
    • Place of Presentation
      Southermpton, United Kingdom
    • Data Source
      KAKENHI-PROJECT-25240036
  • [Presentation] Estimation of causal direction in the presence of latent confounders using a Bayesian LiNGAM mixture model2013

    • Author(s)
      N. Tanaka, S. Shimizu and T. Washio
    • Organizer
      Causality: Perspectives from Different Disciplines
    • Place of Presentation
      Vals (Switzerland)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] K. Kadowaki, S. Shimizu and T. Washio2013

    • Author(s)
      K. Kadowaki, S. Shimizu and T. Washio
    • Organizer
      23rd IEEE International Workshop on Machine Learning for Signal Processing (MLSP2013)
    • Place of Presentation
      Southampton (United Kingdom)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 潜在交絡変数が存在する場合のベイズ的アプローチによる非ガウス因果構造推定法2013

    • Author(s)
      田中直樹, 清水昌平, 鷲尾 隆
    • Organizer
      第27回人工知能学会全国大会
    • Place of Presentation
      富山国際会議場(富山)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 経時データにおける非ガウス性を用いた因果構造探索2013

    • Author(s)
      門脇健人, 清水昌平, 鷲尾隆
    • Organizer
      第27回人工知能学会全国大会
    • Place of Presentation
      富山国際会議場(富山)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] Estimation of causal direction in the presence of latent confounders using a Bayesian LiNGAM mixture model2013

    • Author(s)
      Naoki Tanaka, Shouhei Shimizu and Takashi Washio
    • Organizer
      Causality: Perspectives from different disciplines
    • Place of Presentation
      Vals, Switzerland
    • Invited
    • Data Source
      KAKENHI-PROJECT-25240036
  • [Presentation] 複数データセットによる非ガウス構造方程式モデルの推定2012

    • Author(s)
      清水昌平
    • Organizer
      科研費シンポジウム「生体数理・社会数理の統計科学」
    • Place of Presentation
      早稲田大学(東京)
    • Year and Date
      2012-03-02
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Estimation of causal orders in a linear non-Gaussian acyclic model: a method robust against latent confounders2012

    • Author(s)
      T. Tashiro, S. Shimizu, Aapo Hyvarinen, T. Washio
    • Organizer
      22nd Int. Conf. on Articial Neural Networks (ICANN2012)
    • Place of Presentation
      Lausanne (Switzerland)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 複数データセットによる非ガウス構造方程式モデルの推定2012

    • Author(s)
      清水昌平
    • Organizer
      情報統計力学の最前線ー情報と揺らぎの制御の物理学を目指してー
    • Place of Presentation
      京都大学(京都)(招待講演)
    • Year and Date
      2012-03-21
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Bootstrap confidence intervals in DirectLiNGAM2012

    • Author(s)
      Kittitat Thamvitayakul, Shohei Shimizu, Tsuyoshi Ueno, Takashi Washio and Tatsuya Tashiro
    • Organizer
      RIKD: Workshop on Reliability Issues in Knowledge Discovery, ICDM 2012. The IEEE International Conference on Data Mining
    • Place of Presentation
      Brussels, Belgium
    • Data Source
      KAKENHI-PROJECT-24650069
  • [Presentation] Bootstrap confidence intervals in Direct LINGAM2012

    • Author(s)
      K. Thamvitayakul, S. Shimizu, T. Ueno, T. Washio, T. Tashiro
    • Organizer
      Int. Conf. on Data Mining Workshops (ICDMW2012)
    • Place of Presentation
      Brussels (Belgium)
    • Year and Date
      2012-12-10
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] 非ガウス性を用いた線形非巡回なデータ生成過程部分の発見と同定2012

    • Author(s)
      田代竜也, 清水昌平, 鷲尾隆
    • Organizer
      第26回人工知能学会全国大会
    • Place of Presentation
      山口県教育会館(山口県)
    • Year and Date
      2012-06-15
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] 非ガウス性を用いた線形非巡回なデータ生成過程部分の発見と同定2012

    • Author(s)
      田代竜也, 清水昌平, 鷲尾 隆
    • Organizer
      第26回人工知能学会全国大会
    • Place of Presentation
      山口県教育会館 (山口)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 構造方程式モテ〓ルによる因果構造探索:非カ〓ウス性の利用2012

    • Author(s)
      清水昌平
    • Organizer
      情報統計力学の最前線-情報と揺らぎの制御の物理学を目指して-
    • Place of Presentation
      京都大学(京都)(招待講演)
    • Year and Date
      2012-03-21
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Bootstrap confidence intervals in DirectLiNGAM2012

    • Author(s)
      K. Thamvitayakul, S. Shimizu, T. Ueno, T. Washio, T. Tashiro
    • Organizer
      2012 IEEE 12th International Conference on Data Mining Workshops (ICDMW2012)
    • Place of Presentation
      Brussels (Belgium)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] Bootstrapping confidence intervals in linear non-Gaussian causal model2012

    • Author(s)
      Kittitat Thamvitayakul, 清水昌平 鷲尾隆, 田代竜也
    • Organizer
      第26回人工知能学会全国大会
    • Place of Presentation
      山口県教育会館(山口県)
    • Year and Date
      2012-06-15
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] 非ガウス構造方程式モデルにおける因果順序の推定: 潜在交絡変数に頑健な方法2012

    • Author(s)
      田代竜也, 清水昌平, Aapo Hyvarinen, 鷲尾 隆
    • Organizer
      第3回Latent Dynamicsワークショップ
    • Place of Presentation
      東京大学 (東京)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] Estimation of causal orders in a linear non-Gaussian acyclic model : amethod robust against latent confounders2012

    • Author(s)
      T. Tashiro, S. Shimizu, Aapo Hyvarinen, T. Washio
    • Organizer
      Int. Conf. on Articial Neural Networks(ICANN2012)
    • Place of Presentation
      Lausanne (Switzerland)
    • Year and Date
      2012-09-13
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] 非ガウス性を用いた線形非巡回なデータ生成過程部分の発見と同定2012

    • Author(s)
      田代 竜也, 清水 昌平, 鷲尾 隆
    • Organizer
      2012年人工知能学会全国大会,4B1-R-2-6
    • Place of Presentation
      山口県山口市
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Presentation] 構造方程式モデルによる因果推論: 因果構造探索に関する最近の発展2012

    • Author(s)
      清水昌平
    • Organizer
      日本行動計量学会第40回大会
    • Place of Presentation
      新潟県立大学 (新潟)
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] Bootstrapping confidence intervals in linear non-Gaussian causal model2012

    • Author(s)
      Kittitat Thamvitayakul, 清水昌平, 鷲尾 隆, 田代竜也
    • Organizer
      第26回人工知能学会全国大会
    • Place of Presentation
      山口県教育会館 (山口)
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] 因果構造探索と非ガウス構造方程式モデル2012

    • Author(s)
      清水昌平
    • Organizer
      人工知能学会 第87回 人工知能基本問題研究会 (SIG-FPAI)
    • Place of Presentation
      慶應義塾大学 (神奈川)
    • Invited
    • Data Source
      KAKENHI-PROJECT-24700275
  • [Presentation] Estimation of Causal Orders in a Linear Non-Gaussian Acyclic Model: A Method Robust against Latent Confounders2012

    • Author(s)
      Tatsuya Tashiro, Shohei Shimizu, Aapo Hyv¨arinen, Takashi Washio
    • Organizer
      Artificial Neural Networks and Machine Learning – ICANN 2012, Part I, pp. 491-498
    • Place of Presentation
      Lausanne, Switzerland
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Presentation] Bootstrapping confidence intervals in linear non-Gaussian causal model2012

    • Author(s)
      Thamvitayakul Kittitat, 清水 昌平, 鷲尾 隆, 田代 竜也
    • Organizer
      2012年人工知能学会全国大会
    • Place of Presentation
      山口県山口市
    • Data Source
      KAKENHI-PROJECT-24650069
  • [Presentation] 定常時系列データの非ガウス性を用いたARMAモデルによる変数間決定関係の解析2011

    • Author(s)
      田代竜也, 清水昌平, 河原吉伸, 鷲尾隆
    • Organizer
      第25回人工知能学会全国大会
    • Place of Presentation
      いわて県民情報交流センター(盛岡)
    • Year and Date
      2011-06-02
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] 離散データの因果の同定~2値から、多値への一般化について~2011

    • Author(s)
      鈴木譲, 清水昌平, 鷲尾隆
    • Organizer
      第14回情報論的学習理論ワークショップ
    • Place of Presentation
      奈良女子大学(奈良)
    • Year and Date
      2011-11-10
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] 分割表の独立性に基づく二値データ生成過程の推定法2011

    • Author(s)
      稲積孝紀, 鷲尾隆, 清水昌平, 鈴木譲, 山本章博, 河原吉伸
    • Organizer
      第14回情報論的学習理論ワークショップ
    • Place of Presentation
      奈良女子大学(奈良)
    • Year and Date
      2011-11-10
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Discovering causal structures in binary exclusive-or skew acyclic model2011

    • Author(s)
      T.Inazumi, T.Washio, S.Shimizu, J.Suzuki, A.Yamamoto, Y.Kawahara
    • Organizer
      27th Conf.on Un-certainty in Articial Intelligence
    • Place of Presentation
      Barcelona (Spain)
    • Year and Date
      2011-07-16
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Discovering causal structures in binary exclusive-or skew acyclic models. 27th Conf2011

    • Author(s)
      T. Inazumi, T. Washio, S. Shimizu, J. Suzuki, A. Yamamoto and Y. Kawahara
    • Organizer
      27th Conf. on Uncertainty in Artificial Intelligence(UAI2011)
    • Place of Presentation
      バルセロナ(スペイン)
    • Year and Date
      2011-07-16
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Discovering causal structures in binary exclusive-or skew acyclic models2011

    • Author(s)
      T.Inazumi, T.Washio, S.Shimizu, J.Suzuki, A.Yamamoto and Y.Kawahara
    • Organizer
      Proc. 27th Conf. on Uncertainty in Artificial Intelligence (UAI2011)
    • Place of Presentation
      Barcelona, Spain
    • Year and Date
      2011-07-16
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Presentation] Analyzing relationships between CTARMA and ARMA models2011

    • Author(s)
      Marina Domeshko, 鷲尾隆, 河原吉伸, 清水昌平
    • Organizer
      第25回人工知能学会全国大会
    • Place of Presentation
      いわて県民情報交流センター(盛岡)
    • Year and Date
      2011-06-02
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Discovering Causal Structures in Binary Exclusive-or Skew Acyclic Models2011

    • Author(s)
      Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara
    • Organizer
      UAI2011 : The 27th Conference on Uncertainty in Artificial Intelligence
    • Place of Presentation
      Barcelona, Spain
    • Year and Date
      2011-07-16
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Presentation] 二値データに対するデータ生成過程の推定2011

    • Author(s)
      稲積孝紀, 鷲尾隆, 清水昌平, 鈴木譲, 山本章博, 河原吉伸
    • Organizer
      第25回人工知能学会全国大会
    • Place of Presentation
      いわて県民情報交流センター(盛岡)
    • Year and Date
      2011-06-02
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Non-Gaussian methods for learning linear structural equation models2010

    • Author(s)
      S. Shimizu and Y. Kawahara
    • Organizer
      26th Conference on Uncertainty in Artificial Intelligence(UAI2010)
    • Place of Presentation
      カタナリーナ島(米国)(招待チュートリアル)
    • Year and Date
      2010-07-08
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Use of prior knowledge in a non-Gaussian method for learning linear structural equation models2010

    • Author(s)
      T.Inazumi, S.Shimizu, T.Washio
    • Organizer
      9th Int.Conf.on Latent Variable Analysis and Signal Separation (LVA/ICA2010)
    • Place of Presentation
      Saint-Malo (France)
    • Year and Date
      2010-09-28
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Assessing statistical reliability of LiNGAM via multiscale bootstrap2010

    • Author(s)
      Y.Komatsu, S.Shimizu, H.Shimodaira.
    • Organizer
      Int.Conf.on Artificial Neural Networks (ICANN2010)
    • Place of Presentation
      Thessaloniki (Greece)
    • Year and Date
      2010-09-15
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Use of prior knowledge in a non-Gaussian method for learning linear structural equation models2010

    • Author(s)
      T. Inazumi, S. Shimizu and T. Washio
    • Organizer
      9th Int. Conf. on Latent Variable Analysis and Signal Separation(LVA/ ICA2010)
    • Place of Presentation
      サンマロ(フランス)
    • Year and Date
      2010-09-28
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] An experimental comparison of linear non-Gaussian causal discovery methods and their variants2010

    • Author(s)
      Yasuhiro Sogawa, Shohei Shimizu, Yoshinobu Kawahara, Takashi Washio
    • Organizer
      Proc.of IJCNN2010 : WCCI 2010 IEEE World Congress on Computational Intelligence, Joint Conference on Neural Networks
    • Place of Presentation
      Barcelona, Spain
    • Year and Date
      2010-07-23
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Presentation] データの非正規性を活用する因果構造探索法と事前情報の利用2010

    • Author(s)
      稲積孝紀、十河泰弘、清水昌平、河原吉伸、鷲尾隆
    • Organizer
      第24回人工知能学会全国大会
    • Place of Presentation
      長崎ブリックホール(長崎)
    • Year and Date
      2010-06-09
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Discovery of exogenous variables in data with more variables than observations2010

    • Author(s)
      Y.Sogawa, S.Shimizu, A.Hyvarinen, T.Washio, T.Shimamura, S.Imoto
    • Organizer
      Int.Conf.on Artificial Neural Networks (ICANN2010)
    • Place of Presentation
      Thessaloniki (Greece)
    • Year and Date
      2010-09-17
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] 構造方程式モデルによるデータ生成過程の学習,特に非ガウス性の利用2010

    • Author(s)
      清水昌平
    • Organizer
      第13回情報論的学習理論ワークショップ(IBIS2010)
    • Place of Presentation
      東京大学(東京)
    • Year and Date
      2010-11-04
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Washio. An experimental comparison of linear non-Gaussian causal discovery methods and their variants2010

    • Author(s)
      Y. Sogawa, S. Shimizu, Y. Kawahara and T. Washio
    • Organizer
      Int. Joint Conf. on Neural Networks(IJCNN2010), part of the IEEE World Congress on Computational Intelligence(WCCI2010)
    • Place of Presentation
      バルセロナ(スペイン)
    • Year and Date
      2010-07-23
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models2010

    • Author(s)
      Takanori Inazumi, Shohei Shimizu, Takashi Washio
    • Organizer
      Proc.of LVA/ICA2010 : Ninth International Conference on Latent Variable Analysis and Signal Separation
    • Place of Presentation
      Malo(France)
    • Year and Date
      2010-09-28
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Presentation] ブートストラップ確率の計算誤差を修正するためのマルチスケール・ブートストラップ法:LiNGAM因果構造推定の場合2010

    • Author(s)
      小松勇介, 下平英寿, 清水昌平
    • Organizer
      2010年度 統計関連学会連合大会
    • Place of Presentation
      早稲田大学(東京)
    • Year and Date
      2010-09-06
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Assessing statistical reliability of LiNGAM via multiscale bootstrap2010

    • Author(s)
      Y. Komatsu, S. Shimizu and H. Shimodaira
    • Organizer
      20^<th> Int. Conf. on Artificial Neural Networks(ICANN2010)
    • Place of Presentation
      テッサロニキ(ギリシャ)
    • Year and Date
      2010-09-15
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] ブートストラップ確率の計算誤差を修正するためのマルチスケール・ブートストラップ法: LiNGAM因果構造推定の場合2010

    • Author(s)
      小松勇介、下平英寿、清水昌平
    • Organizer
      2010年度統計関連学会連合大会
    • Place of Presentation
      早稲田大学(東京)
    • Year and Date
      2010-09-06
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Non-Gaussian methods for learning linear structural equation models2010

    • Author(s)
      S.Shimizu, Y.Kawahara
    • Organizer
      The 26th Conference on Uncertainty in Artificial Intelligence (UAI2010)
    • Place of Presentation
      Catalina Island, California (U.S.A).(招待講演)
    • Year and Date
      2010-07-08
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Discovery of Exogenous Variables in Data with More Variables than Observations2010

    • Author(s)
      Yasuhiro Sogawa, Shohei Shimizu, Aapo Hyvarinen, Takashi Washio, Teppei Shimamura, Seiya Imoto
    • Organizer
      Proc.of ICANN2010 : 20th International Conference on Artificial Neural Networks
    • Place of Presentation
      Thessaloniki(Greece)
    • Year and Date
      2010-09-17
    • Data Source
      KAKENHI-PROJECT-22300054
  • [Presentation] Discovery of exogenous variables in data with more variables than observations2010

    • Author(s)
      Y. Sogawa, S. Shimizu, A. Hyvarinen, T. Washio, T. Shimamura and S. Imoto
    • Organizer
      20^<th> Int. Conf. on Artificial Neural Networks(ICANN2010)
    • Place of Presentation
      テッサロニキ(ギリシャ)
    • Year and Date
      2010-09-17
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] An experimental comparison of linear non-Gaussian causal discovery methods and their variants2010

    • Author(s)
      Y.Sogawa, S.Shimizu, Y.Kawahara, T.Washio
    • Organizer
      Int.Joint Conf.on Neural Networks (IJCNN2010), part of the IEEE World Congress on Computational Intelligence (WCCI2010)
    • Place of Presentation
      Barcelona (Spain)
    • Year and Date
      2010-07-23
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] 統計的大規模因果推論の課題と非ガウス性に基づく挑戦2009

    • Author(s)
      鷲尾隆, 清水昌平, 河原吉伸, 猪口明博
    • Organizer
      第75回人工知能学会基本問題研究会(SIG-FPAI), (社)人工知能学会
    • Place of Presentation
      電気通信大学(東京都)
    • Year and Date
      2009-11-13
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] Consistency of penalized risk of boosting methods in binary classification2009

    • Author(s)
      K. Hayashi, S. Shimizu, Y. Kano
    • Organizer
      In New Trends in Psychometrics, Post Proceedings of IMPS2007: the 15th International and 72nd Annual Meeting of the Psychometric Society
    • Place of Presentation
      Tower Hall Funabori(Tokyo)
    • Year and Date
      2009-07-11
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model2009

    • Author(s)
      S. Shimizu, A. Hyvarinen, Y. Kawahara and T. Washio
    • Organizer
      25th Conf. on Uncertainty in Artificial Intelligence(UAI2009)
    • Place of Presentation
      モントリオール(カナダ)
    • Year and Date
      2009-06-21
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] 独立成分分析を用いた外生的発現遺伝子同定解析2009

    • Author(s)
      十河泰弘, 清水昌平, 鷲尾隆, 井元清哉
    • Organizer
      人工知能学会第23回全国大会(JSAI 2009)
    • Place of Presentation
      サンポートホール高松(香川県)
    • Year and Date
      2009-06-18
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] Identification of an Exogenous Variable in a Linear non-Gaussian Structural Equation Model2009

    • Author(s)
      Shohei Shimizu, Aapo Hyvarinen, Yoshinobu Kawahara, Takashi Washio
    • Organizer
      The International Workshop on Data Mining and Statistical Science (DMSS2009)
    • Place of Presentation
      Tokyo Institute of Technology (Tokyo)
    • Year and Date
      2009-07-08
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] マルチスケール・ブートストラップを用いた信頼度計算:LiNGAMによる因果モデル探索の場合2009

    • Author(s)
      小松勇介, 清水昌平, 下平英寿
    • Organizer
      2009年度統計関連学会連合大会
    • Place of Presentation
      同志社大学(京都府
    • Year and Date
      2009-09-07
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] 独立成分分析を用いた外生的発現遺伝子同定解析2009

    • Author(s)
      十河泰弘、清水昌平、鷲尾隆、井元清哉
    • Organizer
      第23回人工知能学会全国大会
    • Place of Presentation
      サンポート高松(高松)
    • Year and Date
      2009-06-18
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] マルチスケール・ブートストラップを用いた信頼度計算: LiNGAMによる因果モデル探索の場合2009

    • Author(s)
      小松勇介、清水昌平、下平英寿
    • Organizer
      2009年度統計関連学会連合大会
    • Place of Presentation
      同志社大学(京都)
    • Year and Date
      2009-09-07
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Identification of an exogenous vriable in a linear non-Gaussian structural equation model2009

    • Author(s)
      S.Shimizu, A.Hyvarinen, Y.Kawahara, T.Washio
    • Organizer
      The Fourth International Workshop on Data-Mining and Statistical Science
    • Place of Presentation
      京大会館(京都府)
    • Year and Date
      2009-07-08
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] Identification of an exogenous variable in a linear non-Gaussian structural equation model2009

    • Author(s)
      S. Shimizu, A. Hyvarinen, Y. Kawahara and T. Washio
    • Organizer
      The Fourth International Workshop on Data-Mining and Statistical Science(DMSS2009)
    • Place of Presentation
      京大会館(京都)
    • Year and Date
      2009-07-08
    • Data Source
      KAKENHI-PROJECT-21700302
  • [Presentation] A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model2009

    • Author(s)
      S. Shimizu, A. Hyvinen, Y. Kawahara, T. Washio
    • Organizer
      Proc. of UAI2009: 25th Conf. on Uncertainty in Artificial Intelligence, Causality II & Graphical Models
    • Place of Presentation
      Montreal(Canada)
    • Year and Date
      2009-06-21
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] Penalized boosting algorithm for mislabeled data (Invited)2008

    • Author(s)
      K. Hayashi, S. Shimizu, Y. Kano
    • Organizer
      IMPS2008: the 73rd Annual Meeting of the Psychometric Society
    • Place of Presentation
      Greensboro(USA)
    • Year and Date
      2008-06-30
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] Penalized boosting algorithm for mislabeled data2008

    • Author(s)
      K. Hayashi, Y. Shimizu, Y. Kano
    • Organizer
      IMPS2008 : the 73rd Annual Meeting of the Psychometric Society (Invited)
    • Place of Presentation
      New Hampshire, USA
    • Year and Date
      2008-06-29
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] Interval estimations based on normalizing transformations by two approaches2008

    • Author(s)
      Y. Konya, S. Shimizu, Y. Kano
    • Organizer
      IMPS2008: the 73rd Annual Meeting of the Psychometric Society
    • Place of Presentation
      New Hampshire(USA)
    • Year and Date
      2008-06-29
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] Interval estimations based on normalizing transformations by two approaches2008

    • Author(s)
      Y. Konya, Y. Shimizu, Y. Kano
    • Organizer
      IMPS2008 : the 73rd Annual Meeting of the Psychometric Society
    • Place of Presentation
      New Hampshire, USA
    • Year and Date
      2008-06-29
    • Data Source
      KAKENHI-PROJECT-19200013
  • [Presentation] 経時データにおける非ガウス性を用いた因果構造探索

    • Author(s)
      門脇健人, 清水昌平, 鷲尾隆
    • Organizer
      第27回人工知能学会全国大会
    • Place of Presentation
      富山国際会議場 (富山県富山市)
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] Estimation of causal direction in the presence of latent confounders using a Bayesian LiNGAM mixture model

    • Author(s)
      N. Tanaka, S. Shimizu, T. Washio
    • Organizer
      Causality: Perspectives from Different Disciplines
    • Place of Presentation
      Hotel Therme Vals (Vals, Switzerland)
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] 潜在交絡変数が存在する場合のベイズ的アプローチによる非ガウス因果構造推定法

    • Author(s)
      田中直樹, 清水昌平, 鷲尾 隆
    • Organizer
      第27回人工知能学会全国大会
    • Place of Presentation
      富山国際会議場 (富山県富山市)
    • Data Source
      KAKENHI-PROJECT-24300106
  • [Presentation] Estimation of causal structures in longitudinal data using non-Gaussianity

    • Author(s)
      K. Kadowaki, S. Shimizu, T. Washio
    • Organizer
      23rd IEEE International Workshop on Machine Learning for Signal Processing (MLSP2013)
    • Place of Presentation
      Chilworth Manor Hotel & Conference Centre (Southampton, United Kingdom)
    • Data Source
      KAKENHI-PROJECT-24300106
  • 1.  WASHIO Takashi (00192815)
    # of Collaborated Projects: 6 results
    # of Collaborated Products: 23 results
  • 2.  KAWAHARA Yoshinobu (00514796)
    # of Collaborated Projects: 5 results
    # of Collaborated Products: 10 results
  • 3.  INOKUCHI Akihiro (70452456)
    # of Collaborated Projects: 4 results
    # of Collaborated Products: 2 results
  • 4.  KANO Yutaka (20201436)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 7 results
  • 5.  Shimodaira Hidetoshi (00290867)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 0 results
  • 6.  IBA Yutaka (30213200)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 0 results
  • 7.  IMOTO Seiya (10345027)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 1 results
  • 8.  OHARA Kouzou (30294127)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 9.  TERMIER Alexandlre (60435823)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 10.  HIGUCHI Tomoyuki (70202273)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 11.  NAKANO Shinya (40378576)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 12.  DEGUCHI Yasuo (20314073)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 13.  HAMAZAKI Toshimitsu (40379243)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 14.  TAKAGI Yoshiji (00231390)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 15.  SUGIMOTO Tomoyuki (70324829)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 16.  TAKAI Keiji (20572019)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 17.  NAITO Kanta (80304252)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 18.  KANAMORI Takafumi (60334546)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 19.  Fukuma Shingo (60706703)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 20.  Michael E.Houle (90399270)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 21.  塩瀬 隆之 (90332759)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 22.  辰巳 明久 (90295634)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 23.  位田 隆一 (40127543)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 24.  青井 貴之 (00546997)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 25.  森崎 隆幸 (30174410)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 26.  須齋 正幸 (40206454)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 27.  磯 博康 (50223053)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 28.  神崎 宣次 (50422910)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 29.  平澤 俊明 (60462230)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 30.  児玉 聡 (80372366)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 31.  佐久間 淳 (90376963)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 32.  秋本 洋平 (20709654)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 33.  福地 一斗 (30838090)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 34.  仙田 涼摩 (70965574)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 35.  KATAYAMA Shota
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 36.  YAMAMOTO Michio
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 1 results
  • 37.  SONG Xinyuan
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 38.  JAMSHIDIAN Mortaza
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 39.  HYVARINEN Aapo
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 1 results
  • 40.  YUAN Ke-hai
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 41.  Ting Kai Ming
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 42.  鈴木 健大
    # of Collaborated Projects: 0 results
    # of Collaborated Products: 1 results

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