• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to previous page

Sugiyama Masashi  杉山 将

… Alternative Names

SUGIYAMA Masashi  杉山 将

Less
Researcher Number 90334515
Other IDs
  • ORCIDhttps://orcid.org/0000-0001-6658-6743
External Links
Affiliation (Current) 2021: 国立研究開発法人理化学研究所, 革新知能統合研究センター, センター長
2021: 東京大学, 大学院新領域創成科学研究科, 教授
Affiliation (based on the past Project Information) *help 2017 – 2020: 東京大学, 大学院新領域創成科学研究科, 教授
2014 – 2016: 東京大学, 新領域創成科学研究科, 教授
2013: 東京工業大学, 大学院・情報理工学研究科, 准教授
2011 – 2013: 東京工業大学, 情報理工学(系)研究科, 准教授
2007 – 2011: 東京工業大学, 大学院・情報理工学研究科, 准教授 … More
2007: Tokyo Institute of Technology, 大学院・情報通工学研究科, 准教授
2006: 東京工業大学, 大学院情報理工学研究科, 助教授
2006: 東京工業大学, 大学院理工学研究科, 助教授
2005: 東京工業大学, 大学院・情報理工学研究科, 助教授
2003: 東工大, 情報理工学研究科, 助手
2002: 東京工業大学, 大学院・情報理工学研究科, 助教授
2001: Tokyo Institute of Technology, Department of Computer Science, Research Associate, 大学院・情報理工学研究科, 助手
2001: 東京工業大学, 大学院・理工学研究科, 助手 Less
Review Section/Research Field
Principal Investigator
Intelligent informatics / Intelligent informatics / Intelligent informatics / Complex systems
Except Principal Investigator
Perception information processing/Intelligent robotics / Perceptual information processing / Intelligent informatics / Intelligent informatics / Complex systems / Basic Section 61010:Perceptual information processing-related
Keywords
Principal Investigator
機械学習 / 強化学習 / 教師付き学習 / 汎化能力 / モデル選択 / 共変量シフト / ロボット制御 / 次元削減 / subspace information criterion (SIC) / 最小二乗学習 … More / 正則化学習 / 再生核ヒルベルト空間 / カーネル法 / 関数近似 / 汎化誤差 / 交差確認法 / ベイズ推定 / ブレインコンピュータインターフェース / 不偏性 / 入力点依存 / 準教師付き学習 / ラベル無しデータ / 学習と知識獲得 / 知能情報処理 / データマイニング / 非定常環境適応 / 重点サンプリング / 重要度重み / 政策反復法 / 政策探索法 / 非定常環境 / 密度比推定 / 予測 / 意志決定 / 特徴選択 / 意思決定 / スパース学習 / ロバスト学習 / 制御理論 / 情報量 / 密度比 / 密度差 / 密度微分 / 教師なし学習 / クラス事前確率推定 / リーマン幾何 / 類似度 / ダイバージェンス / 密度差推定 / 多椀バンディット問題 / ロバスト化 / 多腕バンディット問題 / ロバスト性 / クラウドソーシング / マルチタスク学習 / オンライン学習 … More
Except Principal Investigator
機械学習 / 共変量シフト / 脳信号処理 / マハラノビス計量 / 教師付き学習 / 汎化能力 / 誤差逆伝搬法 / 射影学習族 / 部分空間情報量基準 / SIC / 射影学習 / supervised learning / generalization capability / subspace information criterion / パターン認識 / 共分散行列 / 主成分分析 / ブレインコンピュータインターフェイス / 信号空間の構造 / Mahalanobis 計量 / 幾何学的局所等方独立 / 非対称カーネル法 / コミッティ機械 / ブラインド信号抽出 / 多様体 / 汎化能力推定 / 時空間計量 / Mahalanobis計量 / 最小二乗確率的分類器 / 多様体上のアンサンブル学習 / マルチカーネル適応フィルタ / 制約条件付き最大事後確率識別器 / 拡張カーネル法 / 最小2乗確率的分類器 / 適応的カーネル主成分分析 / Fisher判別分析の修正項 / 線形計画法による最大事後確率識別 / コミッティマシン / 部分カーネル主成分追跡 / Grassmann多様体上の距離 / サポートベクタマシン / 多様体信号処理 / 局所独立方程式 / 局所等方独立方程式 / 計量学習 / 生体信号処理 / ブレイン・コンピュータ・インターフェース / ブレイン・コンピュータ・インターフェイス / 不完全交差学習 / コミティマシン / 記憶学習 / 許容性 / 適用範囲 / ニューラルネットワーク / 過学習 / error back-propagation / memorization learning / admissibility / a family of projection learnings / 部分射影学習 / SL射影学習 / 能動学習 / 個別学習理論 / 学習族の理論 / 追加学習 / projection learning / partial projection learning / family of projection learning / SL projection learning / active learning / 神経科学 / 意思決定 / 強化学習 / 内部モデル / 脳内シュミレーション / 脳内シミュレーション / 作用素多様体 / 局所等方独立 / 信号処理 / ドメイン適応 / 正定値行列 / 相関行列 / 認識機構 / ファイバー束 Less
  • Research Projects

    (15 results)
  • Research Products

    (228 results)
  • Co-Researchers

    (19 People)
  •  Theory for unified expression of recognition mechanisms and its application to machine learningOngoing

    • Principal Investigator
      山下 幸彦
    • Project Period (FY)
      2020 – 2022
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 61010:Perceptual information processing-related
    • Research Institution
      Tokyo Institute of Technology
  •  Theory and Application of Statistical Reinforcement LearningPrincipal InvestigatorOngoing

    • Principal Investigator
      杉山 将
    • Project Period (FY)
      2017 – 2021
    • Research Category
      Grant-in-Aid for Scientific Research (A)
    • Research Field
      Intelligent informatics
    • Research Institution
      The University of Tokyo
  •  Theory of operator manifold and its application to pattern recognition

    • Principal Investigator
      Yukihiko Yamashita
    • Project Period (FY)
      2017 – 2019
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Perceptual information processing
    • Research Institution
      Tokyo Institute of Technology
  •  時間的な変化を伴うデータに対する機械学習手法に関する研究Host Researcher

    • Host Researcher
      杉山 将
    • Project Period (FY)
      2014
    • Research Category
      Grant-in-Aid for JSPS Fellows
    • Research Field
      Intelligent informatics
    • Research Institution
      The University of Tokyo
  •  Manifold signal processing theory concerning metric structure and its application to biological signal processing

    • Principal Investigator
      Yukihiko Yamashita
    • Project Period (FY)
      2014 – 2016
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Perceptual information processing
    • Research Institution
      Tokyo Institute of Technology
  •  Theory and Application of Information-Based Machine LearningPrincipal Investigator

    • Principal Investigator
      Sugiyama Masashi
    • Project Period (FY)
      2013 – 2016
    • Research Category
      Grant-in-Aid for Young Scientists (A)
    • Research Field
      Intelligent informatics
    • Research Institution
      The University of Tokyo
      Tokyo Institute of Technology
  •  Development of Machine Learning Theory for Prediction and Decision Making and Its Realization in Neural NetworksPrincipal Investigator

    • Principal Investigator
      Sugiyama Masashi
    • Project Period (FY)
      2011 – 2015
    • Research Category
      Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
    • Review Section
      Complex systems
    • Research Institution
      The University of Tokyo
      Tokyo Institute of Technology
  •  signal manifold by extended kernel method and its application

    • Principal Investigator
      YUKIHIKO Yamashita
    • Project Period (FY)
      2011 – 2013
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Perception information processing/Intelligent robotics
    • Research Institution
      Tokyo Institute of Technology
  •  Elucidation of the Neral Computation for Prediction and Decision Making

    • Principal Investigator
      Doya Kenji
    • Project Period (FY)
      2011 – 2015
    • Research Category
      Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
    • Review Section
      Complex systems
    • Research Institution
      Okinawa Institute of Science and Technology Graduate University
  •  Machine Learning under Changing EnvironmentsPrincipal Investigator

    • Principal Investigator
      SUGIYAMA Masashi
    • Project Period (FY)
      2008 – 2011
    • Research Category
      Grant-in-Aid for Young Scientists (A)
    • Research Field
      Intelligent informatics
    • Research Institution
      Tokyo Institute of Technology
  •  Machine learning theory based on structure of signal space and its application

    • Principal Investigator
      YAMASHITA Yukihiko
    • Project Period (FY)
      2006 – 2008
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Perception information processing/Intelligent robotics
    • Research Institution
      Tokyo Institute of Technology
  •  入力点に依存した汎化能力推定法に関する研究Principal Investigator

    • Principal Investigator
      杉山 将
    • Project Period (FY)
      2005 – 2007
    • Research Category
      Grant-in-Aid for Young Scientists (B)
    • Research Field
      Intelligent informatics
    • Research Institution
      Tokyo Institute of Technology
  •  教師付き学習におけるモデル選択に関する研究Principal Investigator

    • Principal Investigator
      杉山 将
    • Project Period (FY)
      2002 – 2004
    • Research Category
      Grant-in-Aid for Young Scientists (B)
    • Research Field
      Intelligent informatics
    • Research Institution
      Tokyo Institute of Technology
  •  Theory of Family of Learnings-From a Single Learning to Infinitely Many Learning-

    • Principal Investigator
      OGAWA Hidemitsu
    • Project Period (FY)
      2002 – 2004
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Intelligent informatics
    • Research Institution
      TOKYO INSTITUTE OF TECHNOLOGY
  •  Generalization Capability of Memorization Leaning

    • Principal Investigator
      OGAWA Hidemitsu
    • Project Period (FY)
      1999 – 2001
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Research Field
      Intelligent informatics
    • Research Institution
      Tokyo Institute of Technology

All 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 Other

All Journal Article Presentation Book

  • [Book] Statistical Reinforcement Learning: Modern Machine Learning Approaches.2015

    • Author(s)
      Sugiyama, M.
    • Total Pages
      206
    • Publisher
      Chapman and Hall/CRC
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Book] 機械学習のための確率と統計2015

    • Author(s)
      杉山 将
    • Total Pages
      127
    • Publisher
      講談社
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Book] Statistical Reinforcement Learning: Modern Machine Learning Approaches2015

    • Author(s)
      Sugiyama, M.
    • Total Pages
      206
    • Publisher
      Chapman and Hall/CRC
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Book] Introduction to Statistical Machine Learning.2015

    • Author(s)
      Sugiyama, M.
    • Total Pages
      534
    • Publisher
      Morgan Kaufmann
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Book] Introduction to Statistical Machine Learning2015

    • Author(s)
      Sugiyama, M.
    • Total Pages
      534
    • Publisher
      Morgan Kaufmann
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Book] 異常検知と変化検知2015

    • Author(s)
      井手 剛, 杉山 将
    • Total Pages
      192
    • Publisher
      講談社
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Book] イラストで学ぶ機械学習 : 最小二乗法による識別モデル学習を中心に2013

    • Author(s)
      杉山将
    • Total Pages
      230
    • Publisher
      講談社
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Book] イラストで学ぶ機械学習:最小二乗法による識別モデル学習を中心に,2013

    • Author(s)
      杉山 将
    • Total Pages
      230
    • Publisher
      講談社
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Book] イラストで学ぶ機械学習:最小二乗法による識別モデル学習を中心に2013

    • Author(s)
      杉山 将
    • Total Pages
      230
    • Publisher
      講談社
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Book] イラストで学ぶ機械学習:最小二乗法による識別モデル学習を中心に2013

    • Author(s)
      杉山 将
    • Total Pages
      230
    • Publisher
      講談社
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Book] Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation2012

    • Author(s)
      Sugiyama, M. & Kawanabe, M.
    • Total Pages
      308
    • Publisher
      MIT Press
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Book] Machine Learning in Non-Stationary Environments : Introduction to Covariate Shift Adaptation2012

    • Author(s)
      Sugiyama, M., Kawanabe, M.
    • Total Pages
      308
    • Publisher
      MIT Press
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Book] Machine Learning in Non-Stationary Environments : Introduction to Covariate Shift Adaptation2012

    • Author(s)
      Sugiyama, M. & Kawanabe, M
    • Total Pages
      308
    • Publisher
      MIT Press, Cambridge, MA, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Book] Density Ratio Estimation in Machine Learning,2012

    • Author(s)
      Sugiyama, M., Suzuki, T., & Kanamori, T.
    • Total Pages
      344
    • Publisher
      Cambridge University Press
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Book] Dataset Shift in Machine Learning2009

    • Author(s)
      Quinonero-Candela, J., Sugiyama, M., Schwaighofer, A., Lawrence, N. D.
    • Total Pages
      229
    • Publisher
      MIT Press
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Book] Dataset Shift in Machine Learning2009

    • Author(s)
      Quinonero-Candela, J., Sugiyama, M., Schwaighofer, A., & Lawrence, N. D.
    • Total Pages
      248
    • Publisher
      MIT Press, Cambridge, MA, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Book] Dataset Shift in Machine Learning2009

    • Author(s)
      J. Quionero Candela, M. Sugiyama, A. Schwaighofer and N.D. Lawrence
    • Total Pages
      229
    • Publisher
      MIT Press
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Book] MIT Press, Cambridge, MA, USA2009

    • Author(s)
      Quinonero-Candela, J., Sugiyama, M., Schwaighofer, A., Lawrence, N.D.(Eds.)
    • Publisher
      Dataset Shift in Machine Learning
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Book] Dataset Shift in Machine Learning2009

    • Author(s)
      Quinonero-Candela, J., Sugiyama, M., Schwaighofer, A., & Lawrence, N. D
    • Total Pages
      248
    • Publisher
      MIT Press
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Book] パターン認識と機械学習:ペイズ理論による統計的予測,2007

    • Author(s)
      元田 浩, 栗田 多喜夫, 樋口 知之, 松本 裕治, 村田 昇, (編), 赤穂 昭太郎, 神嶌 敏弘, 杉山 将, 小野田 崇, 池田 和司, 鹿島 久嗣, 賀沢 秀人, 中島 伸一, 竹内 純一, 持橋 大地, 小山 聡, 井手 剛, 篠田 浩一, 山川 宏, (訳)
    • Total Pages
      350
    • Publisher
      シュプリンガー・ジャパン
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Active deep Q-learning with demonstration2020

    • Author(s)
      Chen, S.-A., Tangkaratt, V., Lin, H.-T., & Sugiyama, M.
    • Journal Title

      Machine Learning, to appear

      Volume: -

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Journal Article] Partially zero-shot domain adaptation from incomplete target data with missing classes2020

    • Author(s)
      Masato Ishii, Takeshi Takenouchi, and Masashi Sugiyama
    • Journal Title

      Proceedings of The IEEE Winter Conference on Applications of Computer Vision

      Volume: - Pages: 3052-3060

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-17H01760
  • [Journal Article] Zero-shot domain adaptation based on attribute information2019

    • Author(s)
      Masato Ishii, Takeshi Takenouchi, and Masashi Sugiyama
    • Journal Title

      Proceedings of the 11th Asian Conference on Machine Learning

      Volume: - Pages: 473-488

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-17H01760
  • [Journal Article] Hierarchical reinforcement learning via advantage-weighted information maximization2019

    • Author(s)
      Osa, T., Tangkaratt, V., & Sugiyama, M.
    • Journal Title

      Proceedings of Seventh International Conference on Learning Representations (ICLR2019)

      Volume: -

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Journal Article] Unsupervised domain adaptation based on source-guided discrepancy2019

    • Author(s)
      S. Kuroki, N. Charoenphakdee, H. Bao, J. Honda, I. Sato, and M. Sugiyama
    • Journal Title

      Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI2019)

      Volume: -

    • Data Source
      KAKENHI-PROJECT-17H01760
  • [Journal Article] Imitation learning from imperfect demonstration2019

    • Author(s)
      Wu, Y.-H., Charoenphakdee, N., Bao, H., Tangkaratt, V., & Sugiyama, M.
    • Journal Title

      Proceedings of 36th International Conference on Machine Learning (ICML2019)

      Volume: - Pages: 6818-6827

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Journal Article] Good arm identification via bandit feedback2019

    • Author(s)
      Kano, H., Honda, J., Sakamaki, K., Matsuura, K., Nakamura, A., & Sugiyama, M.
    • Journal Title

      Machine Learning

      Volume: 108 Pages: 721-745

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Journal Article] Good arm identification via bandit feedback.2019

    • Author(s)
      Kano, H., Honda, J., Sakamaki, K., Matsuura, K., Nakamura, A., & Sugiyama, M.
    • Journal Title

      Machine Learning

      Volume: -

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Journal Article] Learning discrete representations via information maximizing self-augmented training2017

    • Author(s)
      W. Hu, T. Miyato, S. Tokui, E. Matsumoto, and M. Sugiyama
    • Journal Title

      Proceedings of 34th International Conference on Machine Learning

      Volume: 70 Pages: 1558-1567

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-17H01760
  • [Journal Article] Class-prior estimation for learning from positive and unlabeled data2017

    • Author(s)
      du Plessis, M. C., Niu, G., & Sugiyama, M.
    • Journal Title

      Machine Learning

      Volume: -

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Generative local metric learning for kernel regression2017

    • Author(s)
      Y.-K. Noh, M. Sugiyama, K.-Y., Kim, F. C. Park, and D. D. Lee
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 30 Pages: 2449-2459

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H01760
  • [Journal Article] Geometry-aware principal component analysis for symmetric positive definite matrices2017

    • Author(s)
      Horev, I., Yger, F., & Sugiyama, M.
    • Journal Title

      Machine Learning

      Volume: -

    • Peer Reviewed / Acknowledgement Compliant / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Least-squares log-density gradient clustering for Riemannian manifolds2017

    • Author(s)
      M. Ashizawa, H. Sasaki, T. Sakai, and M. Sugiyama
    • Journal Title

      Proceedings of 29th International Conference on Artificial Intelligence and Statistics

      Volume: 54 Pages: 537-546

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Journal Article] Regularized multi-task learning for multi-dimensional log-density gradient estimation2016

    • Author(s)
      Yamane, I., Sasaki, H., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 28 Pages: 1388-1410

    • NAID

      110009971442

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Regularized multi-task learning for multi-dimensional log-density gradient estimation2016

    • Author(s)
      I. Yamane, H. Sasaki, and, M. Sugiyama
    • Journal Title

      Neural Computation

      Volume: 28 Pages: 1388-1410

    • DOI

      10.1162/neco_a_00844

    • NAID

      110009971442

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Journal Article] An online policy gradient algorithm for Markov decision processes with continuous states and actions.2016

    • Author(s)
      Ma, Y., Zhao, T., Hatano, K., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 28 Pages: 563-593

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Direct density-derivative estimation2016

    • Author(s)
      Sasaki, H., Noh, Y.-K., Niu, G., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 28 Pages: 1101-1140

    • Peer Reviewed / Acknowledgement Compliant / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Theoretical and experimental analyses of tensor-based regression and classification.2016

    • Author(s)
      Wimalawarne, K., Tomioka, R., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 28 Pages: 686-715

    • Peer Reviewed / Acknowledgement Compliant / Int'l Joint Research
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Model-based reinforcement learning with dimension reduction2016

    • Author(s)
      Tangkaratt, V., Morimoto, J., & Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: 84 Pages: 1-16

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Multitask principal component analysis2016

    • Author(s)
      I. Yamane, F. Yger, M. Berar, M. Sugiyama
    • Journal Title

      Proceedings of the 8th Asian Conference on Machine Learning

      Volume: 63 Pages: 302-317

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Journal Article] Trial and error: Using previous experiences as simulation models in humanoid motor learning.2016

    • Author(s)
      Sugimoto, N., Tangkaratt, V., Wensveen, T., Zhao, T., Sugiyama, M., & Morimoto, J.
    • Journal Title

      IEEE Robotics & Automation Magazine

      Volume: 23 Pages: 96-105

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Computationally efficient class-prior estimation under class balance change using energy distance2016

    • Author(s)
      Kawakubo, H., du Plessis, M. C., & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E99-D Pages: 176-186

    • NAID

      130005116200

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Bandit-based task assignment for heterogeneous crowdsourcing2015

    • Author(s)
      Zhang, H., Ma, Y., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 27 Pages: 2447-2475

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Cross-domain matching with squared-loss mutual information2015

    • Author(s)
      Yamada, M., Sigal, L., Raptis, M., Toyoda, M., Chang, Y., & Sugiyama, M.
    • Journal Title

      IEEE Transactions on Pattern Analysis and Machine Intelligence

      Volume: 37 Pages: 1764-1776

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Importance-weighted covariance estimation for robust common spatial pattern2015

    • Author(s)
      A. Balzi, F. Yger, and M. Sugiyama
    • Journal Title

      Pattern Recognition Letters

      Volume: 68 Pages: 139-145

    • DOI

      10.1016/j.patrec.2015.09.003

    • NAID

      110009971424

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Journal Article] Online direct density-ratio estimation applied to inlier-based outlier detection2015

    • Author(s)
      du Plessis, M. C., Shiino, H., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 27 Pages: 1899-1914

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Direct Density Ratio Estimation with Convolutional Neural Networks with Application in Outlier Detection2015

    • Author(s)
      H. Nam and M. Sugiyama
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E98-D Issue: 5 Pages: 1073-1079

    • DOI

      10.1587/transinf.2014edp7335

      10.1587/transinf.2014EDP7335

    • NAID

      130005067754

    • ISSN
      0916-8532, 1745-1361
    • Language
      English
    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Journal Article] Direct conditional probability density estimation with sparse feature selection.2015

    • Author(s)
      Shiga, M., Tangkaratt, V., & Sugiyama, M.
    • Journal Title

      Machine Learning

      Volume: 100 Pages: 161-182

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] 相互情報量を用いた機械学習とそのロボティクスへの応用2015

    • Author(s)
      杉山 将, 入江 清, 友納 正裕
    • Journal Title

      日本ロボット学会誌

      Volume: 33 Pages: 86-91

    • NAID

      130005065137

    • Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Direct density ratio estimation with convolutional neural networks with application in outlier detection2015

    • Author(s)
      H. Nam, and M. Sugiyama
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E98-D

    • NAID

      130005067754

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Journal Article] Information-theoretic semi-supervised metric learning via entropy regularization.2014

    • Author(s)
      Niu, G., Dai, B., Yamada, M., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 26 Pages: 1717-1762

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] 非定常環境下での学習:共変量シフト適応,クラスバランス変化適応,変化検知.2014

    • Author(s)
      杉山 将, 山田 誠, ドゥ・プレシ マーティヌス・クリストフェル, リウ ソン.
    • Journal Title

      日本統計学会論文誌

      Volume: 44 Pages: 113-136

    • NAID

      110009864639

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Computationally efficient estimation of squared-loss mutual information with multiplicative kernel models.2014

    • Author(s)
      Sakai, T. & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E97-D Pages: 968-971

    • NAID

      110009886357

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Semi-supervised information-maximization clustering.2014

    • Author(s)
      Calandriello, D., Niu, G., & Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: 57 Pages: 103-111

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Semi-supervised learning of class balance under class-prior change by distribution matching2014

    • Author(s)
      du Plessis, M. C. & Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: 50 Pages: 110-119

    • NAID

      110009545983

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Constrained least-squares density-difference estimation.2014

    • Author(s)
      Nguyen, T. D., du Plessis, M. C., Kanamori, T., & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E97-D Pages: 1822-1829

    • NAID

      130004519278

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Statistical analysis of distance estimators with density differences and density ratios2014

    • Author(s)
      Kanamori, T. & Sugiyama, M.
    • Journal Title

      Entropy

      Volume: 16 Pages: 921-942

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Information-maximization clustering based on squared-loss mutual information2014

    • Author(s)
      Sugiyama, M., Niu, G., Yamada, M., Kimura, M., & Hachiya, H.
    • Journal Title

      Neural Computation

      Volume: 26 Pages: 84-131

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Class prior estimation from positive and unlabeled data.2014

    • Author(s)
      du Plessis, M. C. & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E97-D Pages: 1358-1362

    • NAID

      130004519253

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Information-theoretic semi-supervised metric learning via entropy regularization2014

    • Author(s)
      G. Niu, B. Dai, B., M. Yamada, and M. Sugiyama,
    • Journal Title

      Neural Computation

      Volume: 26 Pages: 1717-1762

    • DOI

      10.1162/neco_a_00614

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-26280054
  • [Journal Article] Constrained least-squares density-difference estimation.2014

    • Author(s)
      Nguyen, T. D., du Plessis, M. C., Kanamori, T., & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E97-D Pages: 1822-1829

    • NAID

      130004519278

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Model-based policy gradients with parameter-based exploration by least-squares conditional density estimation.2014

    • Author(s)
      Tangkaratt, V., Mori, S., Zhao, T., Morimoto, J., & Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: 57 Pages: 128-140

    • NAID

      110009713016

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Least-squares independence regression for non-linear causal inference under non-Gaussian noise.2014

    • Author(s)
      Yamada, M., Sugiyama, M., & Sese, J.
    • Journal Title

      Machine Learning

      Volume: 96 Pages: 249-267

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Tree-based ensemble multi-task learning method for classification and regression2014

    • Author(s)
      J. Simm, I. Magrans de Abril, and M. Sugiyama
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E97-D

    • NAID

      130004841806

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] Unsupervised dimension reduction via least-squares quadratic mutual information.2014

    • Author(s)
      Sainui, J. & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E97-D Pages: 2806-2809

    • NAID

      110009971453

    • Peer Reviewed / Acknowledgement Compliant
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Variational Bayesian sparse additive matrix factorization.2013

    • Author(s)
      Nakajima, S., Sugiyama, M., & Babacan, D.
    • Journal Title

      Machine Learning

      Volume: 92 Pages: 319-347

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Densitydifference estimation2013

    • Author(s)
      M. Sugiyama, T. Suzuki, T. Kanamori, T., M. C. du Plessis, S. Liu, and I. Takeuchi
    • Journal Title

      Neural Computation

      Volume: Vol.25,No.10 Pages: 2734-2775

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] 確率分布間の距離推定:機械学習分野における最新動向2013

    • Author(s)
      杉山 将
    • Journal Title

      日本応用数理学会論文誌

      Volume: 23 Pages: 439-452

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] Direct approximation of quadratic mutual information and its application to dependence-maximization clustering.2013

    • Author(s)
      Sainui, J. & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E96-D Pages: 2282-2285

    • NAID

      130004519212

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] High-dimensional feature selection by feature-wise kernelized lasso.2013

    • Author(s)
      Yamada, M., Jitkrittum, W., Sigal, L., Xing, E. P., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 26 Pages: 185-207

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Artist agent: A reinforcement learning approach to automatic stroke generation in oriental ink painting.2013

    • Author(s)
      Xie, N., Hachiya, H., & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E96-D Pages: 1134-1144

    • NAID

      10031193966

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Learning under non-stationarity: Covariate shift and class-balance change.2013

    • Author(s)
      Sugiyama, M., Yamada, M., & du Plessis, M. C.
    • Journal Title

      WIREs Computational Statistics

      Volume: - Pages: 1-13

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Journal Article] Feature selection via l1-penalized squared-loss mutual information.2013

    • Author(s)
      Jitkrittum, W., Hachiya, H., & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E96-D Pages: 1513-1524

    • NAID

      130003370928

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Density Difference Estimation2013

    • Author(s)
      M. Sugiyama, T. Suzuki, T. Kanamori, M. C. du Plessis, S. Liu, and I. Takeuchi
    • Journal Title

      Neural Computation

      Volume: 25 Pages: 2734-2775

    • DOI

      10.1162/neco_a_00492

    • NAID

      110009588474

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069, KAKENHI-PROJECT-24500340, KAKENHI-PROJECT-25730013
  • [Journal Article] Efficient sample reuse in policy gradients with parameter-based exploration.2013

    • Author(s)
      Zhao, T., Hachiya, H., Tangkaratt, V., Morimoto, J., & Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 25 Pages: 1512-1547

    • NAID

      110009545976

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Computationally efficient multi-label classification by least-squares probabilistic classifiers2013

    • Author(s)
      H. Nam, H. Hachiya, and M. Sugiyama
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: Vol.E96-D,No.8 Pages: 1871-1874

    • NAID

      10031100385

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] Infinitesimal annealing for training semi-supervised support vector machines2013

    • Author(s)
      K. Ogawa, M. Imamura, I. Takeuchi, and M. Sugiyama
    • Journal Title

      International Conference on Machine Learning

      Volume: - Pages: 897-905

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] Computationally efficient multi-label classification by least-square probabilistic classifiers2013

    • Author(s)
      H. Nam, H. Hachiya, and M. Sugiyama
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E96-D Pages: 1871-1874

    • NAID

      10031100385

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] 変分ベイズ学習理論の最新動向.2013

    • Author(s)
      中島 伸一, 杉山 将.
    • Journal Title

      日本応用数理学会論文誌

      Volume: 23 Pages: 453-483

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Global analytic solution of fully-observed variational Bayesian matrix factorization.2013

    • Author(s)
      Nakajima, S., Sugiyama, M., Babacan, D., & Tomioka, R.
    • Journal Title

      Journal of Machine Learning Research

      Volume: 14 Pages: 1-37

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Least-squares probabilistic classifier : A computationally efficient alternative to kernel logistic regression2012

    • Author(s)
      M.Sugiyama, H.Hachiya, M.Yamada, J.Simm, H.Nam
    • Journal Title

      Proceedings of International Workshop on Statistical Machine Learning for Speech Processing

      Volume: (CD-ROM) Pages: 1-10

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] Improving importance estimation in pool-based batch active learning for approximate linear regression.2012

    • Author(s)
      Kurihara, N. & Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: 36 Pages: 73-82

    • NAID

      110009545986

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Early stopping heuristics in pool-based incremental active learning for least-squares probabilistic classifier.2012

    • Author(s)
      Kobayashi, T. & Sugiyama, M.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E95-D Pages: 2065-2073

    • NAID

      10031126715

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Analysis and improvement of policy gradient estimation.2012

    • Author(s)
      Zhao, T., Hachiya, H., Niu, G., & Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: 26 Pages: 118-129

    • NAID

      110008746381

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Multi-task approach to reinforcement learning for factored-state Markov decision problems.2012

    • Author(s)
      Simm, J., Sugiyama, M., & Hachiya, H.
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: .E95-D Pages: 2426-2437

    • NAID

      10031142861

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Density difference estimation2012

    • Author(s)
      M. Sugiyama
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 25 Pages: 692-700

    • NAID

      110009588474

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23300069
  • [Journal Article] Reward weighted regression with sample reuse for direct policy search in reinforcement learning2011

    • Author(s)
      Hachiya, H., Peters, J., Sugiyama, M.
    • Journal Title

      Neural Computation

      Volume: 23 Pages: 2798-2832

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Reward weighted regression with sample reuse for direct policy search in reinforcement learning2011

    • Author(s)
      Hachiya, H., Peters, J., & Sugiyama M.
    • Journal Title

      Neural Computation

      Volume: vol.23, no.11 Pages: 2798-2832

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Super-linear convergence of dual augmented Lagrangian algorithm for sparsity regularized estimation2011

    • Author(s)
      Tomioka, R., Suzuki, T., & Sugiyama, M.
    • Journal Title

      Journal of Machine Learning Research

      Volume: 12 Pages: 1537-1586

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Target neighbor consistent feature weighting for nearest neighbor classification2011

    • Author(s)
      Takeuchi, I. & Sugiyama, M.
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 24 Pages: 576-584

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Analysis and improvement of policy gradient estimation.2011

    • Author(s)
      Zhao, T., Hachiya, H., Niu, G., & Sugiyama, M.
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 24 Pages: 262-270

    • NAID

      110008746381

    • Peer Reviewed
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Journal Article] Lighting condition adaptation for perceived age estimation2011

    • Author(s)
      Ueki, K., Sugiyama, M., & Ihara, Y.
    • Journal Title

      Transactions on Information and Systems

      Volume: vol.E94-D, no.2 Pages: 392-395

    • NAID

      130000453904

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Efficient exploration through active learning for value function approximation in reinforcement learning.2010

    • Author(s)
      Akiyama, T., Hachiya, H., Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: 23 Pages: 639-648

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Semi-supervised speaker identification under covariate shift2010

    • Author(s)
      Yamada, M., Sugiyama, M., & Matsui, T.
    • Journal Title

      Signal Processing

      Volume: vol.90, no.8 Pages: 2353-2361

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Semi supervised speaker identification under covariate shift.2010

    • Author(s)
      Yamada, M., Sugiyama, M., Matsui, T.
    • Journal Title

      Signal Processing

      Volume: 90 Pages: 2353-2361

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Application of covariate shift adaptation techniques in brain computer interfaces.2010

    • Author(s)
      Li, Y., Kambara, H., Koike, Y., Sugiyama, M.
    • Journal Title

      IEEE Transactions on Biomedical Engineering vol.57, no.6

      Pages: 1318-1324

    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2010/BIWLDA.pdf

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Efficient exploration through active learning for value function approximation in reinforcement learning2010

    • Author(s)
      Akiyama, T., Hachiya, H., & Sugiyama, M.
    • Journal Title

      Neural Networks

      Volume: vol.23, no.5 Pages: 639-648

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Application of covariate shift adaptation techniques in brain computer interfaces2010

    • Author(s)
      Li, Y., Kambara, H., Koike, Y., & Sugiyama, M.
    • Journal Title

      IEEE Transactions on Biomedical Engineering

      Volume: vol.57, no.6 Pages: 1318-1324

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Semi-supervised speaker identification under covariate shift.2010

    • Author(s)
      Yamada, M., Sugiyama, M., Matsui, T.
    • Journal Title

      Signal Processing vol.90, no.8

      Pages: 2353-2361

    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2010/IWKLR.pdf

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Application of covariate shift adaptation techniques in brain computer interfaces.2010

    • Author(s)
      Li, Y., Kambara, H., Koike, Y., Sugiyama, M.
    • Journal Title

      IEEE Trans.on Biomedical Engineering

      Volume: 57 Pages: 1318-1324

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Efficient exploration through active learning for value function approximation in reinforcement learning.2010

    • Author(s)
      Akiyama, T., Hachiya, H., Sugiyama, M.
    • Journal Title

      NeuralNetworks vol.23, no.5

      Pages: 639-648

    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2010/API.pdf

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Dimensionality reduction for density ratio estimation in high-dimensional spaces2010

    • Author(s)
      Sugiyama, M., Kawanabe, M., & Chui, P. L.
    • Journal Title

      Neural Networks

      Volume: vol.23, no.1 Pages: 44-59

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Adaptive importance sampling for value function approximation in off-policy reinforcement learning2009

    • Author(s)
      Hachiya, H., Akiyama, T., Sugiyama, M., & Peters, J.
    • Journal Title

      Neural Networks

      Volume: vol.22, no.10 Pages: 1399-1410

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] A density-ratio framework for statistical data processing2009

    • Author(s)
      Sugiyama, M., Kanamori, T., Suzuki, T., Hido, S., Sese, J., Takeuchi, I., & Wang, L.
    • Journal Title

      IPSJ Transactions on Computer Vision and Applications

      Volume: vol.1 Pages: 183-208

    • NAID

      130000140299

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Direct importance estimation with Gaussian mixture models2009

    • Author(s)
      Yamada, M. & Sugiyama, M
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: vol.E92-D, no.10 Pages: 2159-2162

    • NAID

      10026811983

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] A least-squares approach to direct importance estimation2009

    • Author(s)
      Kanamori, T., Hido, S., Sugiyama, M.
    • Journal Title

      Journal of Machine Learning Research 10

      Pages: 1391-1445

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Adaptive importance sampling for value function approximation in off-policy reinforcement learning2009

    • Author(s)
      Hachiya, H., Akiyama, T., Sugiyama, M., Peters, J
    • Journal Title

      Neural Networks 22

      Pages: 1399-1410

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] A least-squares approach to direct importance estimation2009

    • Author(s)
      Kanamori, T., Hido, S., & Sugiyama, M.
    • Journal Title

      Journal of Machine Learning Research

      Volume: vol.10 Pages: 1391-1445

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Direct density ratio estimation for large-scale covariate shift adaptation2009

    • Author(s)
      Y. Tsuboi, H, Kashima, S. Hido, S. Bickel, M. Sugiyama
    • Journal Title

      IPSJ Journal 50

      Pages: 1-19

    • NAID

      130000120692

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] A density-ratio framework for statistical data processing2009

    • Author(s)
      Sugiyama, M., Kanamori, T., Suzuki, T., Hido, S., Sese, J., Takeuchi, I., Wang, L.
    • Journal Title

      IPSJ Transactions on Computer Vision and Applications 1

      Pages: 183-208

    • NAID

      130000140299

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Pool-based active learning in approximate linear regression.2009

    • Author(s)
      Sugiyama, M., Nakajima, S.
    • Journal Title

      Machine Learning vol.75, no.3

      Pages: 249-274

    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2009/PALICE.pdf

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] A least-squares approach to direct importance estimation.2009

    • Author(s)
      Kanamori, T., Hido, S., Sugiyama, M.
    • Journal Title

      Journal of Machine Learning Research vol.10 (Jul.)

      Pages: 1391-1445

    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2009/LSIF.pdf

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection2009

    • Author(s)
      T. Kanamori, S. Hido, M. Sugiyama
    • Journal Title

      Advances in Neural Information Processing Systems 21

      Pages: 809-816

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Adaptive importance sampling for value function approximation in off-policy reinforcement learning.2009

    • Author(s)
      Hachiya, H., Akiyama, T., Sugiyama, M., Peters, J.
    • Journal Title

      Neural Networks vol.22, no.10

      Pages: 1399-1410

    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2009/SRPI.pdf

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Direct density ratio estimation for large-scale covariate shift adaptation2009

    • Author(s)
      Tsuboi, Y., Kashima, H., Hido, S., Bickel, S., & Sugiyama, M.
    • Journal Title

      Journal of Information Processing

      Volume: vol.17 Pages: 138-155

    • NAID

      130000120692

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Direct density ratio estimation for large scale covariate shift adaptation2009

    • Author(s)
      Y. Tsuboi, H. Kashima, S. Hido, S. Bickel,and M. Sugiyama
    • Journal Title

      IPSJ Journal 50

      Pages: 1-19

    • NAID

      130000120692

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] A batch ensemble approach to active learning with model selection2009

    • Author(s)
      M. Sugiyama, N. Rubens
    • Journal Title

      Neural Networks 50

      Pages: 1278-1286

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Adaptive importance sampling for value function approximation in off-policy reinforcement learning2009

    • Author(s)
      H. Hachiya, T. Akiyama, M. Sugiyama, J. Peters
    • Journal Title

      Neural Networks (In press)

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] A batch ensemble approach to active learning with model selection2008

    • Author(s)
      Sugiyama, M. & Rubens, N.
    • Journal Title

      Neural Networks

      Volume: vol.21, no.9 Pages: 1278-1286

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Direct importance estimation for covariate shift adaptation2008

    • Author(s)
      M. Sugiyama, T. Suzuki, S. Nakajima, H. Kashima, p. von Beunau, M. Kawanabe
    • Journal Title

      Annals of the Institute of Statistical Mathematics 60

      Pages: 699-746

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Direct importance estimation for covariate shift adaptation.2008

    • Author(s)
      Sugiyama, M., Suzuki, T., Nakajima, S., Kashima, H., von Biinau, P. & Kawanabe, M
    • Journal Title

      Annals of the Institute of Statistical Mathematics 60(4)

      Pages: 699-746

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Direct importance estimation for covariate shift adaptation2008

    • Author(s)
      Sugiyama, M., Suzuki, T., Nakajima, S., Kashima, H., von Bunau, P., & Kawanabe, M.
    • Journal Title

      Annals of the Institute of Statistical Mathematics

      Volume: vol.60, no.4 Pages: 699-746

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] Pool-based agnostic experiment design in linear regression.2008

    • Author(s)
      M. Sugiyama, S. Nakajima
    • Journal Title

      Lecture Notes in Computer Science 5212

      Pages: 406-422

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Direct importance estimation with model selection and its application to covariate shift adaptation2008

    • Author(s)
      M. Sugiyama, S. Nakajima, H. Kashima, von P. Bnau and M. Kawanabe
    • Journal Title

      Advances in Neural Information Processing Systems 20

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Direct importance estimation for covariate shift adaptation.2008

    • Author(s)
      Sugiyama, M., Suzuki, T., Nakajima, S., Kashima, H., von Bunau, P., Kawanabe, M.
    • Journal Title

      Annals of the Institute of Statistical Mathematics vol.60, no.4

      Pages: 699-746

    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2008/KLIEP.pdf

    • Data Source
      KAKENHI-PROJECT-20680007
  • [Journal Article] A batch ensemble approach to active learning with model selection2008

    • Author(s)
      M. Sugiyama and N. Rubens
    • Journal Title

      Neural Networks 21

      Pages: 1278-1286

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Generalization error estimation for non-linear learning methods2007

    • Author(s)
      M. Sugiyama
    • Journal Title

      IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A

      Pages: 1496-1499

    • NAID

      110007538081

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Dimensionality reduction of multimodal labeled data by local Fisher discriminant analysis2007

    • Author(s)
      M. Sugiyama
    • Journal Title

      Journal of Machine Learning Research 8

      Pages: 1027-1061

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Analytic optimization of adaptive ridge parameters based on regularized subspace information criterion.2007

    • Author(s)
      Gokita, S., Sugiyama, M., & Sakurai, K
    • Journal Title

      IEICE Transactions on Fundamentals of Electronic, Communications and Computer Sciences E90-A

      Pages: 2584-2592

    • NAID

      110007537996

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] A new algorithm of non-Gaussian component analysis with radial kernel functions2007

    • Author(s)
      Kawanabe, M., Sugiyama, M., Blanchard, G., Muller, K.-R
    • Journal Title

      Annals of the Institute of Statistical Mathematics vol.59,no.1

      Pages: 57-75

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Covariate shift adaptation by importance weighted cross validation2007

    • Author(s)
      M. Sugiyama, M. Krauledat, K.-R. Mueller
    • Journal Title

      Journal of Machine Learning Research 8

      Pages: 985-1005

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Generalization error estimation for non-linear learning methods.2007

    • Author(s)
      Sugiyama, M.
    • Journal Title

      IEICE Transactions on Fundamentals of Electronics. Communications and Computer Sciences E90-A

      Pages: 1496-1499

    • NAID

      110007538081

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Covariate shift adaptation by importance weighted cross validation.2007

    • Author(s)
      Sugiyama, M., Krauledat, M., & Moller, K.-R.
    • Journal Title

      Journal of Machine Learning Research 8

      Pages: 985-1005

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] 共変量シフト下での教師付き学習2006

    • Author(s)
      杉山 将
    • Journal Title

      日本神経回路学会誌 vol.13,no.3

      Pages: 111-118

    • NAID

      10018266940

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] 共変量シフト下での教師付き学習2006

    • Author(s)
      杉山将
    • Journal Title

      日本神経回路学会誌 13・3

      Pages: 111-118

    • NAID

      10018266940

    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Active learning in approximately linear regression based on conditional expectation generalization error.2006

    • Author(s)
      Sugiyama, M.
    • Journal Title

      Journal of Machine Learning Research 7.Jan

      Pages: 141-166

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Importance-weighted cross-validation for covariate shift2006

    • Author(s)
      Sugiyama, M, Blankertz, B, Krauledat, M, Donehege G, Mller, K.-R
    • Journal Title

      Pattern Recognition, Lecture Notes in Computer Science 47

      Pages: 354-363

    • Data Source
      KAKENHI-PROJECT-18300057
  • [Journal Article] Local Fisher discriminant analysis for supervised dimensionality reduction2006

    • Author(s)
      Sugiyama, M.
    • Journal Title

      Proceedings of 23rd International Conference on Machine Learning, Pittsburgh, Pennsylvania, USA, 2006.6.25-29

      Pages: 905-912

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Importance-weighted cross-validation for covariate shift2006

    • Author(s)
      Sugiyama, M., Blankertz, B., Krauledat, M., Donehege, G., Muller, K.-R
    • Journal Title

      Pattern Recognition, Lecture Notes in Computer Science vol.4147

      Pages: 354-363

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Mixture regression for covariate shift2006

    • Author(s)
      Storkey, A., Sugiyama, M
    • Journal Title

      Advances in Neural Information Processing Systems 19

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Obtaining the best linear unbiased estimator of noisy signals by non-Gaussian component analysis2006

    • Author(s)
      Sugiyama, M., Kawanabe, M., Blanchard, G., Spokoiny, V., Muller, K.-R
    • Journal Title

      Proceedings of 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing, Toulouse, France, 2006.5.14-19. vol,3

      Pages: 608-611

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] An active learning algorithm for approximately correct models.2005

    • Author(s)
      Sugiyama, M.
    • Journal Title

      第8回情報論的学習理論ワークショップ予稿集

      Pages: 57-62

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] 正則化汎化誤差推定量を用いた解析的モデル最適化.2005

    • Author(s)
      櫻井啓介, 杉山 将
    • Journal Title

      画像の認識・理解シンポジウム2005(MIRU2005)論文集

      Pages: 1013-1020

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Generalization error estimation under covariate shift.2005

    • Author(s)
      Sugiyama, M., Mueller, K.-R.
    • Journal Title

      第8回情報論的学習理論ワークショップ予稿集

      Pages: 21-26

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Model selection under covariate shift.2005

    • Author(s)
      Sugiyama, M., Mueller, K.-R.
    • Journal Title

      Artificial Neural Networks : Formal Models and Their Applications 3697

      Pages: 235-240

    • Data Source
      KAKENHI-PROJECT-17700142
  • [Journal Article] Trading variance reduction with unbiasedness : The regularized subspace information criterion for robust model selection in kernel regression2004

    • Author(s)
      M.Sugiyama, M.Kawanabe, K.-R.Muller
    • Journal Title

      Neural Computation 16(59

      Pages: 1077-1104

    • Description
      「研究成果報告書概要(欧文)」より
    • Data Source
      KAKENHI-PROJECT-14380158
  • [Journal Article] Perturbation analysis of a generalization error estimator2004

    • Author(s)
      M.Sugiyama, Y.Okabe, H.Ogawa
    • Journal Title

      Neural Information Processing 2・2

      Pages: 33-38

    • Description
      「研究成果報告書概要(和文)」より
    • Data Source
      KAKENHI-PROJECT-14380158
  • [Journal Article] Trading variance reduction with unbiasedness : The regularized subspace information criterion for robust model selection in kernel regression2004

    • Author(s)
      M.Sugiyama, M.Kawanabe, K.-R.Muller
    • Journal Title

      Neural Computation 16・5

      Pages: 1077-1104

    • Description
      「研究成果報告書概要(和文)」より
    • Data Source
      KAKENHI-PROJECT-14380158
  • [Journal Article] Perturbation analysis of a generalization error estimator2004

    • Author(s)
      M.Sugiyama, Y.Okabe, H.Ogawa
    • Journal Title

      Neural Information Processing 2(2)

      Pages: 33-38

    • Description
      「研究成果報告書概要(欧文)」より
    • Data Source
      KAKENHI-PROJECT-14380158
  • [Journal Article] Adaptive importance sampling for value function approximation in off-policy reinforcement learning

    • Author(s)
      Hachiya, H., Akiyama, T., Sugiyama, M., & Peters, J
    • Journal Title

      Neural Network

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Dueling bandits with qualitative feedback.2019

    • Author(s)
      Xu, L., Honda, J., & Sugiyama, M.
    • Organizer
      AAAI Conference on Artificial Intelligence (AAAI2019)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Bayesian posterior approximation via greedy particle optimization.2019

    • Author(s)
      Futami, F., Cui, Z., Sato, I., & Sugiyama, M.
    • Organizer
      AAAI Conference on Artificial Intelligence (AAAI2019)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Fully adaptive algorithm for pure exploration in linear bandits2018

    • Author(s)
      Xu, L., Honda, J., & Sugiyama, M.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Guide actor-critic for continuous control2018

    • Author(s)
      Tangkaratt, V., Abdolmaleki, A., & Sugiyama, M.
    • Organizer
      International Conference on Learning Representations (ICLR2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Analysis of minimax error rate for crowdsourcing and its application to worker clustering model.2018

    • Author(s)
      Imamura, H., Sato, I., & Sugiyama, M.
    • Organizer
      International Conference on Machine Learning (ICML2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Variational inference for Gaussian process with panel count data.2018

    • Author(s)
      Ding, H., Lee, Y., Sato, I., & Sugiyama, M.
    • Organizer
      Conference on Uncertainty in Artificial Intelligence (UAI2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Continuous-time value function approximation in reproducing kernel Hilbert spaces.2018

    • Author(s)
      Ohnishi, M., Yukawa, M., Johansson, M., & Sugiyama, M.
    • Organizer
      Neural Information Processing Systems (NeurIPS2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Bayesian nonparametric Poisson-process allocation for time-sequence modeling2018

    • Author(s)
      Ding, H., Khan, M. E., Sato, I., & Sugiyama, M.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Fully adaptive algorithm for pure exploration in linear bandits.2018

    • Author(s)
      Xu, L., Honda, J., & Sugiyama, M.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Hierarchical policy search via return-weighted density estimation2018

    • Author(s)
      Osa, T. & Sugiyama, M.
    • Organizer
      AAAI Conference on Artificial Intelligence (AAAI2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Bayesian nonparametric Poisson-process allocation for time-sequence modeling.2018

    • Author(s)
      Ding, H., Khan, M. E., Sato, I., & Sugiyama, M.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Guide actor-critic for continuous control.2018

    • Author(s)
      Tangkaratt, V., Abdolmaleki, A., & Sugiyama, M.
    • Organizer
      International Conference on Learning Representations (ICLR2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Variational inference based on robust divergences2018

    • Author(s)
      Futami, F., Sato, I., & Sugiyama, M.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Lipschitz-margin training: Scalable certification of perturbation invariance for deep neural networks.2018

    • Author(s)
      Tsuzuku, Y., Sato, I., & Sugiyama, M.
    • Organizer
      Neural Information Processing Systems (NeurIPS2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Good arm identification from bandit feedback2017

    • Author(s)
      Kano, H., Honda, J., Sakamaki, K., Matsuura, K., Nakamura, A., & Sugiyama, M.
    • Organizer
      2017 Workshop on Information-Based Induction Sciences (IBIS2017)
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Policy search with high-dimensional context variables2017

    • Author(s)
      Tangkaratt, V., van Hoof, H., Parisi, S., Neumann, G., Peters, J., & Sugiyama, M.
    • Organizer
      Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI2017)
    • Place of Presentation
      San Francisco, California, USA
    • Year and Date
      2017-02-04
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Expectation propagation for t-exponential family using q-algebra2017

    • Author(s)
      Futami, F., Sato, I., & Sugiyama, M.
    • Organizer
      Neural Information Processing Systems (NIPS2017)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H00757
  • [Presentation] Least-squares log-density gradient clustering for Riemannian manifolds2017

    • Author(s)
      Ashizawa, M., Sasaki, H., Sakai, T., & Sugiyama, M.
    • Organizer
      29th International Conference on Artificial Intelligence and Statistics (AISTATS2017)
    • Place of Presentation
      Fort Lauderdale, Florida, USA
    • Year and Date
      2017-04-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Semi-supervised sufficient dimension reduction under class-prior change2016

    • Author(s)
      Kawakubo, H. & Sugiyama, M.
    • Organizer
      Conference on Technologies and Applications of Artificial Intelligence (TAAI2016)
    • Place of Presentation
      Hsinchu, Taiwan
    • Year and Date
      2016-11-25
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Geometry-aware stationary subspace analysis2016

    • Author(s)
      Horev, I., Yger, F., & Sugiyama, M.
    • Organizer
      8th Asian Conference on Machine Learning (ACML2016)
    • Place of Presentation
      Hamilton, New Zealand
    • Year and Date
      2016-11-16
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Modal regression via direct log-density derivative estimation2016

    • Author(s)
      Sasaki, H., Ono, Y., & Sugiyama, M.
    • Organizer
      23rd International Conference on Neural Information Processing (ICONIP2016)
    • Place of Presentation
      Kyoto, Japan
    • Year and Date
      2016-10-16
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Non-Gaussian component analysis with log-density gradient estimation2016

    • Author(s)
      Sasaki, H., Niu, G., & Sugiyama, M.
    • Organizer
      19th International Conference on Artificial Intelligence and Statistics (AISTATS2016)
    • Place of Presentation
      Cadiz, Spain
    • Year and Date
      2016-05-09
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Regularized policy gradients: Direct variance reduction in policy gradient estimation.2015

    • Author(s)
      Zhao, T., Niu, G., Xie, N., Yang, J., & Sugiyama, M.
    • Organizer
      Asian Conference on Machine Learning (ACML2015)
    • Place of Presentation
      Hong Kong, China
    • Year and Date
      2015-11-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Sufficient dimension reduction via direct estimation of the gradients of logarithmic conditional densities.2015

    • Author(s)
      Sasaki, H., Tangkaratt, V., & Sugiyama, M.
    • Organizer
      Asian Conference on Machine Learning (ACML2015)
    • Place of Presentation
      Hong Kong, China
    • Year and Date
      2015-11-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Sufficient dimension reduction via direct estimation of the gradients of logarithmic conditional densities2015

    • Author(s)
      Sasaki, H., Tangkaratt, V., & Sugiyama, M.
    • Organizer
      Asian Conference on Machine Learning (ACML2015)
    • Place of Presentation
      Hong Kong, China
    • Year and Date
      2015-11-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Stroke-based stylization learning and rendering with inverse reinforcement learning.2015

    • Author(s)
      Xie, N., Zhao, T., Tian, F., Zhang, X., & Sugiyama, M.
    • Organizer
      International Joint Conference on Artificial Intelligence (IJCAI2015)
    • Place of Presentation
      Buenos Aires, Argentina
    • Year and Date
      2015-07-25
    • Int'l Joint Research
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Direct density-derivative estimation and its application in KL-divergence approximation.2015

    • Author(s)
      Sasaki, H., Noh, Y.-K., & Sugiyama, M.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2015)
    • Place of Presentation
      San Diego, California, USA
    • Year and Date
      2015-05-09
    • Int'l Joint Research
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Target shift adaptation in supervised learning2015

    • Author(s)
      Nguyen, T. D., du Plessis, M. C., & Sugiyama, M.
    • Organizer
      Asian Conference on Machine Learning (ACML2015)
    • Place of Presentation
      Hong Kong, China
    • Year and Date
      2015-11-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Geometry-aware principal component analysis for symmetric positive definite matrices2015

    • Author(s)
      Horev, I., Yger, F., & Sugiyama, M.
    • Organizer
      Asian Conference on Machine Learning (ACML2015)
    • Place of Presentation
      Hong Kong, China
    • Year and Date
      2015-11-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Geometry-aware principal component analysis for symmetric positive definite matrices.2015

    • Author(s)
      Horev, I., Yger, F., & Sugiyama, M.
    • Organizer
      Asian Conference on Machine Learning (ACML2015)
    • Place of Presentation
      Hong Kong, China
    • Year and Date
      2015-11-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Class-prior estimation for learning from positive and unlabeled data2015

    • Author(s)
      du Plessis, M. C., Niu, G., & Sugiyama, M.
    • Organizer
      Asian Conference on Machine Learning (ACML2015)
    • Place of Presentation
      Hong Kong, China
    • Year and Date
      2015-11-20
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Squared-loss mutual information regularization.2013

    • Author(s)
      Niu, G., Jitkrittum, W., Dai, B., Hachiya, H., & Sugiyama, M.
    • Organizer
      30th International Conference on Machine Learning (ICML2013)
    • Place of Presentation
      Atlanta, Georgia, USA
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Clustering unclustered data: Unsupervised binary labeling of two datasets having different class balances.2013

    • Author(s)
      du Plessis, M. C., Niu, G., & Sugiyama, M.
    • Organizer
      Conference on Technologies and Applications of Artificial Intelligence (TAAI2013),
    • Place of Presentation
      Taipei, Taiwan
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Global solver and its efficient approximation for variational Bayesian low-rank subspace clustering.2013

    • Author(s)
      Nakajima, S., Takeda, A., Babacan, D., Sugiyama, M., & Takeuchi, I.
    • Organizer
      Neural Information Processing Systems (NIPS2013)
    • Place of Presentation
      Lake Tahoe, Nevada
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Parametric task learning.2013

    • Author(s)
      Takeuchi, I., Hongo, T., Sugiyama, M., & Nakajima, S.
    • Organizer
      Neural Information Processing Systems (NIPS2013)
    • Place of Presentation
      Lake Tahoe, Nevada
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Fast learning rate of multiple kernel learning: Trade-off between sparsity and smoothness.2012

    • Author(s)
      Suzuki, T. & Sugiyama, M.
    • Organizer
      Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS2012),
    • Place of Presentation
      La Palma, Canary Islands
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Perfect dimensionality recovery by variational Bayesian PCA.2012

    • Author(s)
      Nakajima, S., Tomioka, R., Sugiyama, M., & Babacan, D.
    • Organizer
      Neural Information Processing Systems (NIPS2012),
    • Place of Presentation
      Lake Tahoe, Nevada, USA
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Feature selection via l1-penalized squared-loss mutual information2012

    • Author(s)
      Jitkrittum, W., Hachiya, H., & Sugiyama, M.
    • Organizer
      電子情報通信学会IBISML研究会, pp.139-146
    • Place of Presentation
      東京
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Artist agent: A reinforcement learning approach to automatic stroke generation in oriental ink painting.2012

    • Author(s)
      Xie, N., Hachiya, H., & Sugiyama, M.
    • Organizer
      29th International Conference on Machine Learning (ICML2012),
    • Place of Presentation
      Edinburgh, Scotland
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Sparse additive matrix factorization for robust PCA and its generalization.2012

    • Author(s)
      Nakajima, S., Sugiyama, M., & Babacan, D.
    • Organizer
      the Fourth Asian Conference on Machine Learning (ACML2012),
    • Place of Presentation
      Singapore
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Perceived age estimation under lighting condition change by covariate shift adaptation2010

    • Author(s)
      Ueki, K., Sugiyama, M., & Ihara, Y.
    • Organizer
      In Proceedings of 20th International Conference on Pattern Recognition(ICPR2010)
    • Place of Presentation
      Istanbul, Turkey
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Perceived age estimation under lighting condition change by covariate shift adaptation.2010

    • Author(s)
      Ueki, K., Sugiyama, M., Ihara, Y.
    • Organizer
      20th International Conferenceon Pattern Recognition (ICPR2010)
    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2010/ICPR2010a.pdf

    • Place of Presentation
      Istanbul, Turkey
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Automatic audio tagging using covariate shift adaptation2010

    • Author(s)
      Wichern, G., Yamada, M., Thornburg, H., Sugiyama, M., & Spanias, A.
    • Organizer
      In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP2010)
    • Place of Presentation
      Dallas, Texas, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Perceived age estimation under lighting condition change by covariate shift adaptation.2010

    • Author(s)
      Ueki, K., Sugiyama, M., Ihara, Y.
    • Organizer
      20th International Conference on Pattern Recognition(ICPR2010)
    • Place of Presentation
      イスタンブール,トルコ
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Efficient sample reuse in EM-based policy search.2009

    • Author(s)
      Hachiya, H., Peters, J., Sugiyama, M.
    • Organizer
      European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases(ECML-PKDD2009)
    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2009/ECML-PKDD2009.pdf

    • Place of Presentation
      Bled, Slovenia
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Active policy iteration : Efficient exploration through active learning for value function approximation in reinforcement learning2009

    • Author(s)
      Akiyama, T., Hachiya, H., Sugiyama, M.
    • Organizer
      Twenty-First International Joint Conference on Artificial Intelligence(IJCAI2009)
    • Place of Presentation
      Pasadena, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Active policy iteration: Efficient exploration through active learning for value function approximation in reinforcement learning.2009

    • Author(s)
      Akiyama, T., Hachiya, H., Sugiyama, M.
    • Organizer
      Twenty-FirstInternational Joint Conference onArtificial Intelligence (IJCAI2009)
    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2009/IJCAI2009.pdf

    • Place of Presentation
      Pasadena, California
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Covariate shift adaptation for semi-supervised speaker identification2009

    • Author(s)
      Yamada, M., Sugiyama, M., & Matsui, T.
    • Organizer
      In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP2009)
    • Place of Presentation
      Taipei, Taiwan
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Efficient sample reuse in EM-based policy search2009

    • Author(s)
      Hachiya, H., Peters, J., & Sugiyama, M.
    • Organizer
      Presented at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases(ECML-PKDD2009)
    • Place of Presentation
      Berlin, Springer, Bled, Slovenia
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] A framework of adaptive brain computer interfaces2009

    • Author(s)
      Li, Y., Koike, Y., & Sugiyama, M.
    • Organizer
      In Proceedings of the 2nd International Conference on BioMedical Engineering and Informatics(BMEI09)
    • Place of Presentation
      Tianjin, China
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Active policy iteration : Efficient exploration through active learning for value function approximation in reinforcement learning2009

    • Author(s)
      Akiyama, T., Hachiya, H., & Sugiyama, M
    • Organizer
      In Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence(IJCAI2009)
    • Place of Presentation
      Pasadena, California, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection2008

    • Author(s)
      Kanamori, T., Hido, S., Sugiyama, M.
    • Organizer
      Neural Information Processing Systems (NIPS2008)
    • URL

      http://sugiyama-www.cs.titech.ac.jp/~sugi/2008/NIPS2008.pdf

    • Place of Presentation
      Vancouver, Canada
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Efficient direct density ratio estimation for non-stationarity adaptation and outlier detection2008

    • Author(s)
      Kanamori, T., Hido, S., & Sugiyama, M.
    • Organizer
      In D. Koller, D. Schuurmans, Y. Bengio, and L. Botton(Eds.), Advances in Neural Information Processing Systems 21,(Presented at Neural Information Processing Systems(NIPS2008), Vancouver, British Columbia
    • Place of Presentation
      Cambridge, MA, MIT Press, Canada, Dec
    • Year and Date
      2008-08-13
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Direct density ratio estimation for large-scale covariate shift adaptation2008

    • Author(s)
      Tsuboi, Y., Kashima, H., Hido, S., Bickel, S., & Sugiyama, M.
    • Organizer
      Proceedings of the Eighth SIAM International Conference on Data Mining(SDM2008)
    • Place of Presentation
      Atlanta, Georgia, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Direct importance estimation---A new versatile tool for statisti cal pattern recognition2008

    • Author(s)
      Sugiyama, M., Kanamori, T, Suzuki, T., Hido, S., Sese, J., Takeuchi, I., & Wang, L
    • Organizer
      Meeting on Image Recognition and Understanding 2008 (MIRU2008)
    • Place of Presentation
      長野
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Semi-supervised speaker identification under covariate shift2008

    • Author(s)
      Yamada, M. & Sugiyama, M
    • Organizer
      The Third International Workshop on Data-Mining and Statistical Science (DMSS2008)
    • Place of Presentation
      東京
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Pool-based agnostic experiment design in linear regression2008

    • Author(s)
      Sugiyama, M. & Nakajima, S
    • Organizer
      Presented at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases(ECML-PKDD2008)
    • Place of Presentation
      Berlin, Springer, Antwerp, Belgium
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Active learning with model selection in linear regression2008

    • Author(s)
      Sugiyama, M. & Rubens, N
    • Organizer
      Proceedings of the Eighth SIAM International Conference on Data Mining(SDM2008)
    • Place of Presentation
      Atlanta, Georgia, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Adaptive importance sampling with automatic model selection in value function approximation2008

    • Author(s)
      Hachiya, H., Akiyama, T., Sugiyama, M., & Peters, J
    • Organizer
      Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence(AAAI2008)
    • Place of Presentation
      Chicago, Illinois, USA
    • Data Source
      KAKENHI-PROJECT-20680007
  • [Presentation] Direct importance estimation with model selection and its application to covariate shift adaptation.2007

    • Author(s)
      Sugiyama, M., Nakajima, S., Kashim a, H., von Bunau, P. & Kawanabe, M.
    • Organizer
      Advances in Neural Information Processing Systems
    • Place of Presentation
      バンクーバー,カナダ
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Presentation] KuUback-Leibler importance estimation procedure for covariate shift adaptation.2007

    • Author(s)
      Sugiyama, M., Nakajima, S., Kashima, H., von Bunau, P.& Kawanabe, M
    • Organizer
      the International Workshop on Data-Mining and Statistical Sciences
    • Place of Presentation
      東京,日本
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Presentation] Supervised learning under covariate shift.2007

    • Author(s)
      Sugiyama, M.
    • Organizer
      13th Symposium on Sensing via Image Information,
    • Place of Presentation
      横浜,日本
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Presentation] Value function approximation on non-linear manifolds for robot motor control2007

    • Author(s)
      M. Sugiyama, H. Hachiya, C. Towell, S. Vijayakumar
    • Organizer
      2007 IEEE International Conference on Robotics and Automation
    • Place of Presentation
      Rome, Italy
    • Year and Date
      2007-04-12
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Presentation] Direct importance estimation with model selection and its application to covariate shift adaptation2007

    • Author(s)
      M. Sugiyama, S. Nakajima, H. Kashima, von P. Bnueau, M. Kawanabe
    • Organizer
      21th Annual Conference on Neural Information Processing Systems
    • Place of Presentation
      Vancouver, Canada
    • Year and Date
      2007-12-04
    • Data Source
      KAKENHI-PROJECT-18300057
  • [Presentation] Asymptotic Bayesian generalization error when training and test distributions are different.2007

    • Author(s)
      Yamazaki, K., Kawanabe, M., Watanabe, S. Sugiyama, M, & Muller, K.-R.
    • Organizer
      24th International Conference on Machine Learning
    • Place of Presentation
      オレゴン,アメリカ
    • Data Source
      KAKENHI-PROJECT-17700142
  • [Presentation] Bias reduction and metric learning for nearest-neighbor estimation of Kullback-Leibler divergence.

    • Author(s)
      Noh, Y.-K., Sugiyama, M., Liu, S., du Plessis, M. C., Park, F. C., & Lee, D. D.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2014)
    • Place of Presentation
      Reykjavik, Iceland
    • Year and Date
      2014-04-22 – 2014-04-24
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Intrinsic principal component analysis for symmetric positive definite matrices.

    • Author(s)
      Horev, I, Yger, F., & Sugiyama, M.
    • Organizer
      Workshop on Information-Based Induction Sciences (IBIS2014)
    • Place of Presentation
      Nagoya, Japan
    • Year and Date
      2014-11-16 – 2014-11-19
    • Data Source
      KAKENHI-PROJECT-14F04730
  • [Presentation] Transductive learning with multi-class volume approximation.

    • Author(s)
      Niu, G., Dai, B., du Plessis, M. C., & Sugiyama, M.
    • Organizer
      International Conference on Machine Learning (ICML2014)
    • Place of Presentation
      Beijing, China,
    • Year and Date
      2014-06-21 – 2014-06-26
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Analysis of learning from positive and unlabeled data.

    • Author(s)
      du Plessis, M. C., Niu, G., & Sugiyama, M.
    • Organizer
      Neural Information Processing Systems (NIPS2014)
    • Place of Presentation
      Montreal, Quebec, Canada
    • Year and Date
      2014-12-08 – 2014-12-11
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] An online policy gradient algorithm for continuous state and action Markov decision processes.

    • Author(s)
      Ma, Y., Zhao, T., Hatano, K., & Sugiyama, M.
    • Organizer
      European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD2014)
    • Place of Presentation
      Nancy, France
    • Year and Date
      2014-09-15 – 2014-09-19
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Transductive learning with multi-class volume approximation.

    • Author(s)
      Niu, G., Dai, B., du Plessis, M. C., & Sugiyama, M.
    • Organizer
      International Conference on Machine Learning (ICML2014)
    • Place of Presentation
      Beijing, China
    • Year and Date
      2014-06-21 – 2014-06-26
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Analysis of empirical MAP and empirical partially Bayes: Can they be alternatives to variational Bayes?

    • Author(s)
      Nakajima, S. & Sugiyama, M.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2014)
    • Place of Presentation
      Reykjavik, Iceland
    • Year and Date
      2014-04-22 – 2014-04-24
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Importance-weighted covariance estimation for robust common spatial pattern.

    • Author(s)
      Balzi, A., Yger, F., & Sugiyama, M.
    • Organizer
      Workshop on Information-Based Induction Sciences (IBIS2014)
    • Place of Presentation
      Nagoya, Japan
    • Year and Date
      2014-11-16 – 2014-11-19
    • Data Source
      KAKENHI-PROJECT-14F04730
  • [Presentation] Clustering via mode seeking by direct estimation of the gradient of a log-density.

    • Author(s)
      Sasaki, H., Hyvarinen, A., & Sugiyama, M.
    • Organizer
      European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD2014)
    • Place of Presentation
      Nancy, France
    • Year and Date
      2014-09-15 – 2014-09-19
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Bias reduction and metric learning for nearest-neighbor estimation of Kullback-Leibler divergence.

    • Author(s)
      Noh, Y.-K., Sugiyama, M., Liu, S., du Plessis, M. C., Park, F. C., & Lee, D. D.
    • Organizer
      International Conference on Artificial Intelligence and Statistics (AISTATS2014)
    • Place of Presentation
      Reykjavik, Iceland
    • Year and Date
      2014-04-22 – 2014-04-24
    • Data Source
      KAKENHI-PROJECT-25700022
  • [Presentation] Clustering via mode seeking by direct estimation of the gradient of a log-density.

    • Author(s)
      Sasaki, H., Hyvarinen, A., & Sugiyama, M.
    • Organizer
      European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD2014)
    • Place of Presentation
      Nancy, France
    • Year and Date
      2014-09-15 – 2014-09-19
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Analysis of variational Bayesian latent Dirichlet allocation: Weaker sparsity than MAP.

    • Author(s)
      Nakajima, S., Sato, I., Sugiyama, M., Watanabe, K., & Kobayashi, H.
    • Organizer
      Neural Information Processing Systems (NIPS2014)
    • Place of Presentation
      Montreal, Quebec, Canada
    • Year and Date
      2014-12-08 – 2014-12-11
    • Data Source
      KAKENHI-PLANNED-23120004
  • [Presentation] Efficient reuse of previous experiences in humanoid motor learning.

    • Author(s)
      Sugimoto, N., Tangkaratt, V., Wensveen, T., Zhao, T., Sugiyama, M., & Morimoto, J.
    • Organizer
      IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS2014)
    • Place of Presentation
      Madrid, Spain
    • Year and Date
      2014-11-18 – 2014-11-20
    • Data Source
      KAKENHI-PLANNED-23120004
  • 1.  YAMASHITA Yukihiko (90220350)
    # of Collaborated Projects: 5 results
    # of Collaborated Products: 0 results
  • 2.  TANAKA Toshihisa (70360584)
    # of Collaborated Projects: 5 results
    # of Collaborated Products: 0 results
  • 3.  WASHIZAWA Yoshikazu (10419880)
    # of Collaborated Projects: 5 results
    # of Collaborated Products: 0 results
  • 4.  OGAWA Hidemitsu (50016630)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 2 results
  • 5.  KUMAZAWA Itsuo (70186469)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 0 results
  • 6.  MORIMOTO Jun (10505986)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 4 results
  • 7.  HIRABAYASHI Akira (50272688)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 8.  Doya Kenji (80188846)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 9.  SAKAGAMI Masamichi (10225782)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 10.  OKAMOTO Hitoshi (40183769)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 11.  SHIBATA Tomohiro (40359873)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 12.  OKADA Mitsuhiro (30224025)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 13.  HIKIDA Takatoshi (70421378)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 14.  KIMURA Minoru (40118451)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 15.  IMAI Mutsumi (60255601)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 16.  TAKAHASHI Hidehiko (60415429)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 17.  YGER Florian
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 2 results
  • 18.  SUZUKI Taiji
    # of Collaborated Projects: 0 results
    # of Collaborated Products: 1 results
  • 19.  金森 敬文
    # of Collaborated Projects: 0 results
    # of Collaborated Products: 1 results

URL: 

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi