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Deepening and applications of sparse modeling by approaches of semiparametric Bayesian inference

Planned Research

Project AreaInitiative for High-Dimensional Data-Driven Science through Deepening of Sparse Modeling
Project/Area Number 25120012
Research Category

Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)

Allocation TypeSingle-year Grants
Review Section Complex systems
Research InstitutionThe Institute of Statistical Mathematics

Principal Investigator

Fukumizu Kenji  統計数理研究所, 数理・推論研究系, 教授 (60311362)

Co-Investigator(Kenkyū-buntansha) 鈴木 大慈  東京大学, 大学院情報理工学系研究科, 准教授 (60551372)
西山 悠  電気通信大学, 大学院情報理工学研究科, 助教 (60586395)
冨岡 亮太  東京大学, 情報理工学(系)研究科, 助教 (70518282)
Co-Investigator(Renkei-kenkyūsha) NISHIYAMA Yu  電気通信大学, 大学院情報理工学研究科, 助教 (60586395)
LIU Song  統計数理研究所, 統計的機械学習研究センター, 特任助教 (80760579)
Project Period (FY) 2013-06-28 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥52,390,000 (Direct Cost: ¥40,300,000、Indirect Cost: ¥12,090,000)
Fiscal Year 2017: ¥10,790,000 (Direct Cost: ¥8,300,000、Indirect Cost: ¥2,490,000)
Fiscal Year 2016: ¥10,920,000 (Direct Cost: ¥8,400,000、Indirect Cost: ¥2,520,000)
Fiscal Year 2015: ¥11,180,000 (Direct Cost: ¥8,600,000、Indirect Cost: ¥2,580,000)
Fiscal Year 2014: ¥11,440,000 (Direct Cost: ¥8,800,000、Indirect Cost: ¥2,640,000)
Fiscal Year 2013: ¥8,060,000 (Direct Cost: ¥6,200,000、Indirect Cost: ¥1,860,000)
Keywordsスパースモデリング / セミパラメトリック / ベイズ推論 / 最適化 / アルゴリズム
Outline of Final Research Achievements

Filtering problems aims at estimating the current unobserved state variable from the unknown dynamics of the unobserved state variables and indirect observations. We consider filtering under the assumption that the observation model is uncertain and not able to be modeled easily, and proposed effective algorithms in such difficult situations. We confirmed the advantage of the proposed algorithms over existing relevant methods. We also studied fast methods for complex sparse modeling, and proposed an optimization methods that achieves the best convergence rate theoretically.

Report

(6 results)
  • 2017 Annual Research Report   Final Research Report ( PDF )
  • 2016 Annual Research Report
  • 2015 Annual Research Report
  • 2014 Annual Research Report
  • 2013 Annual Research Report
  • Research Products

    (99 results)

All 2018 2017 2016 2015 2014 2013 Other

All Int'l Joint Research (9 results) Journal Article (43 results) (of which Int'l Joint Research: 11 results,  Peer Reviewed: 40 results,  Open Access: 29 results,  Acknowledgement Compliant: 16 results) Presentation (38 results) (of which Int'l Joint Research: 12 results,  Invited: 21 results) Book (2 results) Remarks (6 results) Funded Workshop (1 results)

  • [Int'l Joint Research] University College London/Oxford University/University of Bristol(英国)

    • Related Report
      2017 Annual Research Report
  • [Int'l Joint Research] Max Planck Institute(ドイツ)

    • Related Report
      2017 Annual Research Report
  • [Int'l Joint Research] Mahidol University(タイ)

    • Related Report
      2017 Annual Research Report
  • [Int'l Joint Research] Pennsylvania State University(米国)

    • Related Report
      2017 Annual Research Report
  • [Int'l Joint Research] Universite Paris 6(フランス)

    • Related Report
      2017 Annual Research Report
  • [Int'l Joint Research] University of College London/University of Oxford(英国)

    • Related Report
      2016 Annual Research Report
  • [Int'l Joint Research] Pennsylvania State University(米国)

    • Related Report
      2016 Annual Research Report
  • [Int'l Joint Research] University College London/University of Oxford(英国)

    • Related Report
      2015 Annual Research Report
  • [Int'l Joint Research] Max Planck Inst. for Intellignet Systems(ドイツ)

    • Related Report
      2015 Annual Research Report
  • [Journal Article] Generalized ridge estimator and model selection criteria in multivariate linear regression2018

    • Author(s)
      Mori Yuichi、Suzuki Taiji
    • Journal Title

      Journal of Multivariate Analysis

      Volume: 165 Pages: 243-261

    • DOI

      10.1016/j.jmva.2017.12.006

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables2018

    • Author(s)
      M. Takada, T. Suzuki, H. Fujisawa
    • Journal Title

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

      Volume: 84 Pages: 454-463

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models2018

    • Author(s)
      A. Nitanda, T. Suzuki
    • Journal Title

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

      Volume: 84 Pages: 1008-1016

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Fast generalization error bound of deep learning from a kernel perspective2018

    • Author(s)
      T. Suzuki
    • Journal Title

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

      Volume: 84 Pages: 1397-1406

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] A Linear-Time Kernel Goodness-of-Fit Test2017

    • Author(s)
      Jitkrittum, W., Xu, W., Szabo, Z., Fukumizu, K. and Gretton, A.
    • Journal Title

      Advances in Neural Information Processing Systems (NIPS 2017)

      Volume: 30

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Trimmed Density Ratio Estimation2017

    • Author(s)
      Liu, S., Takeda, A., Suzuki, T. and Fukumizu, K.
    • Journal Title

      Advances in Neural Information Processing Systems (NIPS 2017)

      Volume: 30

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization2017

    • Author(s)
      T. Murata, T. Suzuki
    • Journal Title

      Advances in Neural Information Processing Systems (NIPS2017)

      Volume: 30

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Kernel Mean Embedding of Distributions: A Review and Beyond2017

    • Author(s)
      Krikamol Muandet, Kenji Fukumizu, Bharath K. Sriperumbudur, Bernhard Schoelkopf
    • Journal Title

      Foundations and Trends in Machine Learning

      Volume: 10 Issue: 1-2 Pages: 1-141

    • DOI

      10.1561/2200000060

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Post Selection Inference with Kernels2017

    • Author(s)
      M. Yamada, Y. Umezu, K. Fukumizu, I. Takeuchi
    • Journal Title

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

      Volume: 84 Pages: 152-160

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Learning sparse structural changes in high-dimensional Markov networks2017

    • Author(s)
      Song Liu, Kenji Fukumizu, and Taiji Suzuki
    • Journal Title

      Behaviormetrika

      Volume: 44(1) Issue: 1 Pages: 265-286

    • DOI

      10.1007/s41237-017-0014-z

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Unsupervised group matching with application to cross-lingual topic matching without alignment information2017

    • Author(s)
      Tomoharu Iwata, Motonobu Kanagawa, Tsutomu Hirao, Kenji Fukumizu
    • Journal Title

      Data Mining and Knowledge Discovery

      Volume: 31 Issue: 2 Pages: 350-370

    • DOI

      10.1007/s10618-016-0470-1

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Characteristic Kernels and Infinitely Divisible Distributions2016

    • Author(s)
      Yu Nishiyama, Kenji Fukumizu
    • Journal Title

      Journal of Machine Learning Research

      Volume: 17(180) Pages: 1-28

    • Related Report
      2016 Annual Research Report
  • [Journal Article] Convergence guarantees for kernel-based quadrature rules in misspecified settings2016

    • Author(s)
      Motonobu Kanagawa, Barath K. Sriperumbudur, Kenji Fukumizu
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 30 Pages: 3288-3296

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Kernel Mean Shrinkage Estimators2016

    • Author(s)
      Krikamol Muandet, Bharath Sriperumbudur, Kenji Fukumzu, Arthur Gretton, Bernhard Schoelkopf
    • Journal Title

      Journal of Machine Learning Research

      Volume: 17(48): Pages: 1-41

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Structure Learning of Partitioned Markov Networks2016

    • Author(s)
      Song Liu, Taiji Suzuki , Masashi Sugiyama, Kenji Fukumizu
    • Journal Title

      Proceedings of The 33rd International Conference on Machine Learning

      Volume: - Pages: 439-448

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Gaussian process nonparametric tensor estimator and its minimax optimality2016

    • Author(s)
      Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami
    • Journal Title

      Proceedings of The 33rd International Conference on Machine Learning

      Volume: - Pages: 1632-1641

    • Related Report
      2016 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Structure Learning of Partitioned Markov Networks2016

    • Author(s)
      Song Liu, Taiji Suzuki, Masashi Sugiyama, and Kenji Fukumizu
    • Journal Title

      Proc. 33rd International Conference on Machine Learning

      Volume: 1 Pages: 1-9

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Support Consistency of Direct Sparse-Change Learning in Markov Networks2016

    • Author(s)
      Song Liu, Suzuki Taiji, Raissa Relator, Jun Sese, Masashi Sugiyama, and Kenji Fukumizu
    • Journal Title

      Annals of Statistics

      Volume: 2016 Pages: 34-34

    • NAID

      110009971454

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] Kernel Mean Shrinkage Estimators2016

    • Author(s)
      Krikamol Muandet, Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Schölkopf
    • Journal Title

      Journal of Machine Learning Research

      Volume: 17(48) Pages: 1-41

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Filtering with State-Observation Examples via Kernel Monte Carlo Filter2016

    • Author(s)
      Motonobu Kanagawa, Yu Nishiyama, Arthur Gretton, and Kenji Fukumizu
    • Journal Title

      Neural Computation

      Volume: 28 Issue: 2 Pages: 382-444

    • DOI

      10.1162/neco_a_00806

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] System Identification and Parameter Estimation in Mathematical Medicine: Examples Demonstrated for Prostate Cancer2016

    • Author(s)
      Yoshito Hirata, Kai Morino, Taiji Suzuki, Qian Guo, Hiroshi Fukuhara, and Kazuyuki Aihara
    • Journal Title

      Quantitative Biology

      Volume: 4(1) Issue: 1 Pages: 13-19

    • DOI

      10.1007/s40484-016-0059-0

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Bayes method for low rank tensor estimation2016

    • Author(s)
      Taiji Suzuki and Heishiro Kanagawa
    • Journal Title

      Journal of Physics: Conference Series: International Meeting on ”High-Dimensional Data Driven Science” (HD3-2015)

      Volume: 699(1) Pages: 012020-012020

    • DOI

      10.1088/1742-6596/699/1/012020

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] The Nonparametric Kernel Bayes Smoother2016

    • Author(s)
      Yu Nishiyama, Amir Hossein Afsharinejad, Shunsuke Naruse, Byron Boots, Le Song
    • Journal Title

      Proceedings of the 19th International Conference on Artificial Intelligence and Statistics

      Volume: 1

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Computing functions of random variables via reproducing kernel Hilbert space representations2015

    • Author(s)
      Bernhard Scholkopf, Krikamol Muandet, Kenji Fukumizu, Stefan Harmeling, Jonas Peters
    • Journal Title

      Statistics and Computing

      Volume: 25(4) Issue: 4 Pages: 755-766

    • DOI

      10.1007/s11222-015-9558-5

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Higher-Order Regularized Kernel Canonical Correlation Analysis2015

    • Author(s)
      Md. Ashad Alam and Kenji Fukumizu
    • Journal Title

      Int. J. Patt. Recogn. Artif. Intell.

      Volume: 29 Issue: 04 Pages: 1551005-1551005

    • DOI

      10.1142/s0218001415510052

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
  • [Journal Article] Stochastic Alternating Direction Method of Multipliers for Structured Regularization2015

    • Author(s)
      Taiji Suzuki
    • Journal Title

      Journal of Japan Society of Computational Statistics

      Volume: 28 Pages: 105-124

    • NAID

      130005434004

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] カーネルベイズスムージングとカーネル平均Toolboxの作成2015

    • Author(s)
      西山悠
    • Journal Title

      第25回日本神経回路学会全国大会予稿集

      Volume: 1 Pages: 60-61

    • Related Report
      2015 Annual Research Report
  • [Journal Article] Convergence rate of Bayesian tensor estimator and its minimax optimality2015

    • Author(s)
      Taiji Suzuki
    • Journal Title

      JMLR Workshop and Conference Proceedings:The 32nd International Conference on Machine Learning (ICML2015)

      Volume: 37 Pages: 1273-1282

    • Related Report
      2015 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Kernel-Based Information Criterion2015

    • Author(s)
      Somayeh Danafar, Kenji Fukumizu, Faustino Gomez
    • Journal Title

      Computer and Information Science

      Volume: 8 Issue: 1 Pages: 10-24

    • DOI

      10.5539/cis.v8n1p10

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] A Consistent Method for Graph Based Anomaly Localization2015

    • Author(s)
      Satoshi Hara, Tetsuro Morimura, Toshihiro Takahashi, Hiroki Yanagisawa, Taiji Suzuki
    • Journal Title

      Journal of Machine Learning Research, Workshop & Conference Proceedings (ICML2014)

      Volume: 38 Pages: 333-341

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Output Kernel Learning Methods2014

    • Author(s)
      Francesco Dinuzzo, Cheng Soon Ong, Kenji Fukumizu
    • Journal Title

      Regularization, Optimization, Kernels, and Support Vector Machines

      Volume: 1 Pages: 359-370

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Monte Carlo Filtering using Kernel Embedding of Distribution2014

    • Author(s)
      M. Kanagawa, Y. Nishiyama, A. Gretton, and K. Fukumizu
    • Journal Title

      Proceedings of the 29th AAAI Conference on Artificial Intelligence

      Volume: 1 Pages: 1897-1903

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Kernel Mean Estimation and Stein Effect2014

    • Author(s)
      Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur, Arthur Gretton, Bernhard Schoelkopf
    • Journal Title

      Journal of Machine Learning Research, Workshop & Conference Proceedings (ICML2014)

      Volume: 32 Pages: 10-18

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Recovering Distributions from Gaussian RKHS Embeddings2014

    • Author(s)
      Motonobu Kanagawa and Kenji Fukumizu
    • Journal Title

      Journal of Machine Learning Research, Workshop & Conference Proceedings (AISTATS 2014)

      Volume: 33 Pages: 457-465

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Support Consistency of Direct Sparse-Change Learning in Markov Networks2014

    • Author(s)
      Song Liu, Taiji Suzuki, and Masashi Sugiyama
    • Journal Title

      The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI2015)

      Volume: 1 Pages: 2785-2791

    • NAID

      110009971454

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers2014

    • Author(s)
      Taiji Suzuki
    • Journal Title

      Journal of Machine Learning Research, Workshop and Conference Proceedings

      Volume: 32 Pages: 736-744

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Gradient-based kernel dimension reduction for regression2014

    • Author(s)
      Fukumizu, K. and Chenlei, L.
    • Journal Title

      Journal of the American Statistical Association

      Volume: 109(505) Issue: 505 Pages: 359-370

    • DOI

      10.1080/01621459.2013.838167

    • Related Report
      2013 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Recovering Distributions from Gaussian RKHS Embeddings2014

    • Author(s)
      Kanagawa, M. and Fukumizu, K.
    • Journal Title

      Journal of Machine Learning Research, W&CP (Proc. AISTATS 2014)

      Volume: 33 Pages: 457-465

    • Related Report
      2013 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Ryota Tomioka, and Taiji Suzuki: Convex Tensor Decomposition via Structured Schatten Norm Regularization.2014

    • Author(s)
      Tomioka, R. and Suzuki, T.
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 26 Pages: 1331-1339

    • Related Report
      2013 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Hyperparameter Selection in Kernel Principal Component Analysis2014

    • Author(s)
      Alam, A. MD and Fukumizu, K.
    • Journal Title

      Journal of Computer Science

      Volume: 10(7) Issue: 7 Pages: 1139-1150

    • DOI

      10.3844/jcssp.2014.1139.1150

    • Related Report
      2013 Annual Research Report
    • Peer Reviewed
  • [Journal Article] (2013) Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels2013

    • Author(s)
      Fukumizu, K., Song, L. and Gretton, A.
    • Journal Title

      Journal of Machine Learning Research

      Volume: 14 Pages: 3753-3783

    • Related Report
      2013 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Sejdinovic, D., Sriperumbudur, B., Gretton, A. and Fukumizu, K.2013

    • Author(s)
      4. Equivalence of distance-based and RKHS-based statistics in hypothesis testing
    • Journal Title

      Annals of Statistics

      Volume: 41(5) Pages: 2263-2702

    • Related Report
      2013 Annual Research Report
    • Peer Reviewed
  • [Journal Article] カーネル平均埋め込みによる分布統計量の計算 ~ 密度関数,信頼区間,モーメント推定への応用 ~2013

    • Author(s)
      金川元信, 福水健次
    • Journal Title

      電子情報通信学会技術報告

      Volume: IBISML 113(286) Pages: 147-154

    • Related Report
      2013 Annual Research Report
  • [Presentation] Generalization Error and Compressibility of Deep Learning via Kernel Analysis2018

    • Author(s)
      Taiji Suzuki
    • Organizer
      Tokyo Deep Learning Workshop (Deep Learning: Theory, Algorithms, and Applications)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Generalization error bound of Bayesian deep learning: a kernel perspective2017

    • Author(s)
      Taiji Suzuki
    • Organizer
      2017 Probabilistic Graphical Model Workshop: Structure, Sparsity and High-dimensionality
    • Place of Presentation
      東京
    • Year and Date
      2017-02-22
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Developments on Learning Changes between Graphical Models2017

    • Author(s)
      Song Liu
    • Organizer
      2017 Probabilistic Graphical Model Workshop: Structure, Sparsity and High-dimensionality
    • Place of Presentation
      東京
    • Year and Date
      2017-02-22
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Taxonomy Matching between Asteroids and Meteorites: Supervised Clustering Approach2017

    • Author(s)
      Fukumizu, K., Saito, Y., Miyamoto, H., Niihara, T. and Peng, H.
    • Organizer
      High-Dimensional Data-Driven Science (HD3-2017)
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] 機械学習技術の進展とその数理基盤2017

    • Author(s)
      鈴木大慈
    • Organizer
      数理システムユーザーコンファレンス
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] Generalization error analysis of deep learning and its application to network structure determination2017

    • Author(s)
      Taiji Suzuki
    • Organizer
      French-Japanese Workshop on Deep Learning and Artificial Intelligence
    • Related Report
      2017 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] 構造のある機械学習問題における最適化技法2017

    • Author(s)
      鈴木大慈
    • Organizer
      第29回RAMPシンポジウム, 企画セッション「機械学習と最適化」
    • Related Report
      2017 Annual Research Report
    • Invited
  • [Presentation] Convergence guarantees for kernel-based quadrature rules in misspecified settings2016

    • Author(s)
      Motonobu Kanagawa, Barath K. Sriperumbudur, Kenji Fukumizu
    • Organizer
      Neural Information Processing Systems 30
    • Place of Presentation
      バルセロナ
    • Year and Date
      2016-12-05
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Structure Learning of Partitioned Markov Networks2016

    • Author(s)
      Song Liu, Taiji Suzuki , Masashi Sugiyama, Kenji Fukumizu
    • Organizer
      The 33rd International Conference on Machine Learning
    • Place of Presentation
      New York
    • Year and Date
      2016-06-20
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Gaussian process nonparametric tensor estimator and its minimax optimality2016

    • Author(s)
      Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami
    • Organizer
      The 33rd International Conference on Machine Learning
    • Place of Presentation
      New York
    • Year and Date
      2016-06-20
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Structure Learning of Partitioned Markov Networks2016

    • Author(s)
      Song Liu, Taiji Suzuki, Masashi Sugiyama, and Kenji Fukumizu
    • Organizer
      33rd International Conference on Machine Learning
    • Place of Presentation
      New York
    • Year and Date
      2016-06-19
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research
  • [Presentation] カーネル法の最前線2016

    • Author(s)
      福水健次
    • Organizer
      第19回情報論的学習理論ワークショップ チュートリアル
    • Place of Presentation
      京都
    • Related Report
      2016 Annual Research Report
    • Invited
  • [Presentation] Partitioned Markov Networks2016

    • Author(s)
      Song Liu, Taiji Suzuki , Masashi Sugiyama, Kenji Fukumizu
    • Organizer
      MIRU2016 第19回画像の認識・理解シンポジウム
    • Place of Presentation
      浜松
    • Related Report
      2016 Annual Research Report
    • Invited
  • [Presentation] Kernel Mean Particle Filter with Intractable Likelihoods2015

    • Author(s)
      Kenji Fukumizu, Motonobu Kanagawa, and Yoshimasa Uematsu
    • Organizer
      NIPS 2015 Workshop: ABC in Montreal
    • Place of Presentation
      Montreal, Canada
    • Year and Date
      2015-12-11
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 確率的最適化から始める機械学習入門2015

    • Author(s)
      鈴木大慈
    • Organizer
      IBIS2015チュートリアル
    • Place of Presentation
      つくば
    • Year and Date
      2015-11-28
    • Related Report
      2015 Annual Research Report
    • Invited
  • [Presentation] kNNを用いたカーネルベイズの計算量削減法の検討2015

    • Author(s)
      苗村智行, 都築俊介, 西山悠
    • Organizer
      第18回情報論的学習理論ワークショップ(IBIS2015)
    • Place of Presentation
      つくば
    • Year and Date
      2015-11-25
    • Related Report
      2015 Annual Research Report
  • [Presentation] 再生核ヒルベルト空間を用いた確率分布の表現とそのデータ解析への応用2015

    • Author(s)
      福水健次
    • Organizer
      数理解析研究所研究集会
    • Place of Presentation
      京都
    • Year and Date
      2015-10-07
    • Related Report
      2015 Annual Research Report
    • Invited
  • [Presentation] Gaussian process methods for high dimensional learning2015

    • Author(s)
      鈴木大慈
    • Organizer
      統計関連学会連合大会
    • Place of Presentation
      岡山大学
    • Year and Date
      2015-09-06
    • Related Report
      2015 Annual Research Report
  • [Presentation] Kernel Mean Particle Filter with Intractable Likelihoods2015

    • Author(s)
      Kenji Fukumizu, Motonobu Kanagawa, and Yoshimasa Uematsu
    • Organizer
      2015 International Workshop on Spatial and Temporal Modeling from Statistical, Machine Learning and Engineering perspectives (STM2015)
    • Place of Presentation
      東京
    • Year and Date
      2015-07-13
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research / Invited
  • [Presentation] Nonparametric Smoothing on State Space Models with Kernel Mean Embeddings2015

    • Author(s)
      Yu Nishiyama, Amir Hossein Afsharinejad, Shunsuke Naruse, Byron Boots, Le Song
    • Organizer
      1st Symposium on Intelligent Systems in Science and Industry (SISSI)
    • Place of Presentation
      Tuebingen, Germany
    • Year and Date
      2015-07-12
    • Related Report
      2015 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Statistical Machine Learning in the Era of Data2015

    • Author(s)
      Kenji Fukumizu
    • Organizer
      UK-Japan Big Data Workshop
    • Place of Presentation
      Tokyo
    • Year and Date
      2015-02-26
    • Related Report
      2014 Annual Research Report
    • Invited
  • [Presentation] セミパラメトリック推論とスパースモデリング2014

    • Author(s)
      福水健次
    • Organizer
      新学術領域研究「スパースモデリングの深化と高次元データ駆動科学の創成」2014年度公開シンポジウム
    • Place of Presentation
      東京工業大学(すずかけ台)
    • Year and Date
      2014-12-15 – 2014-12-17
    • Related Report
      2014 Annual Research Report
    • Invited
  • [Presentation] Model-based Kernel Sum Rule with Applications to State Space Models2014

    • Author(s)
      Yu Nishiyama, Motonobu Kanagawa, Arthur Gretton, Kenji Fukumizu
    • Organizer
      Neural Information Processing Systems (NIPS) Workshop
    • Place of Presentation
      Montreal, Canada
    • Year and Date
      2014-12-12
    • Related Report
      2014 Annual Research Report
  • [Presentation] Score Matching Estimation with Infinite Dimensional Exponential Family2014

    • Author(s)
      Kenji Fukumizu
    • Organizer
      Coop-Math Workshop: Information Geometry for Machine Learning
    • Place of Presentation
      理研(和光)
    • Year and Date
      2014-12-03 – 2014-12-05
    • Related Report
      2014 Annual Research Report
  • [Presentation] カーネル法とスパースモデリング ~ カーネル法によるセミパラメトリック推論 ~2014

    • Author(s)
      福水健次
    • Organizer
      研究集会「地球科学と疎性モデリング」
    • Place of Presentation
      東大
    • Year and Date
      2014-11-14
    • Related Report
      2014 Annual Research Report
    • Invited
  • [Presentation] 正定値カーネルを用いた条件付き確率密度推定2014

    • Author(s)
      金川元信,鈴木大慈,福水健次
    • Organizer
      統計関連学会連合大会
    • Place of Presentation
      東京
    • Year and Date
      2014-09-14
    • Related Report
      2014 Annual Research Report
  • [Presentation] カーネル法と確率分布の無限分解可能性2014

    • Author(s)
      西山悠
    • Organizer
      日本応用数理学会 2014年度年会
    • Place of Presentation
      政策研究大学院大学
    • Year and Date
      2014-09-05
    • Related Report
      2014 Annual Research Report
    • Invited
  • [Presentation] Monte Carlo Filter with Kernel Mean Embedding2014

    • Author(s)
      Kenji Fukumizu
    • Organizer
      International Workshop on Spatial and Temporal Modeling from Statistical, Machine Learning and Engineering perspectives (STM2014)
    • Place of Presentation
      Tokyo
    • Year and Date
      2014-07-28 – 2014-07-29
    • Related Report
      2014 Annual Research Report
    • Invited
  • [Presentation] Risk Bounds of Convex and Bayes Tensor Estimators: Near Optimal Rate without Strong Convexity2014

    • Author(s)
      Taiji Suzuki
    • Organizer
      International Workshop on Spatial and Temporal Modeling from Statistical, Machine Learning and Engineering perspectives (STM2014)
    • Place of Presentation
      Tokyo
    • Year and Date
      2014-07-28 – 2014-07-29
    • Related Report
      2014 Annual Research Report
    • Invited
  • [Presentation] Measuring Dependence and Conditional Dependence with Kernels2014

    • Author(s)
      Kenji Fukumizu
    • Organizer
      International Conf. Machine Learning 2014, Causality Workshop
    • Place of Presentation
      Beijing
    • Year and Date
      2014-06-25 – 2014-06-26
    • Related Report
      2014 Annual Research Report
    • Invited
  • [Presentation] Nonparametric Bayesian Inference with Positive Definite Kernels,2014

    • Author(s)
      Fukumizu, K.
    • Organizer
      Workshop on Mathematical Approaches to Large-Dimensional Data Analysis
    • Place of Presentation
      東京
    • Related Report
      2013 Annual Research Report
  • [Presentation] カーネル法によるノンパラメトリックなベイズ推論2014

    • Author(s)
      福水健次
    • Organizer
      研究会:神経科学と統計科学の対話 4
    • Place of Presentation
      東京
    • Related Report
      2013 Annual Research Report
    • Invited
  • [Presentation] マルチプルカーネル学習とスパース推定の統計的性質2014

    • Author(s)
      鈴木大慈
    • Organizer
      日本数学会年会
    • Place of Presentation
      東京
    • Related Report
      2013 Annual Research Report
    • Invited
  • [Presentation] カーネル平均埋め込みによる分布統計量の計算 ~ 密度関数,信頼区間,モーメント推定への応用 ~2013

    • Author(s)
      金川元信, 福水健次
    • Organizer
      第16回情報論的学習理論ワークショップ
    • Place of Presentation
      東京
    • Related Report
      2013 Annual Research Report
  • [Presentation] 無限分解可能分布におけるカーネル平均の検討2013

    • Author(s)
      西山悠, 福水健次
    • Organizer
      第16回情報論的学習理論ワークショップ
    • Place of Presentation
      東京
    • Related Report
      2013 Annual Research Report
  • [Presentation] Higher-order Regularized Kernel CCA,2013

    • Author(s)
      Alam,MD, A. and Fukumizu, K.
    • Organizer
      The 12th International Conference on Machine Learning and Applications (ICMLA'13)
    • Place of Presentation
      Florida, USA
    • Related Report
      2013 Annual Research Report
  • [Presentation] Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers.2013

    • Author(s)
      Suzuki, T.
    • Organizer
      OPT2013, NIPS workshop "Optimization for Machine Learning
    • Place of Presentation
      Lake Tahoe, USA
    • Related Report
      2013 Annual Research Report
  • [Presentation] Dual Averaging and Proximal Gradient Descent for Online Alternating Direction Multiplier Method2013

    • Author(s)
      Suzuki, T.
    • Organizer
      The Sixth Workshop on Information Theoretic Methods in Science and Engineering (WITMSE2013).
    • Place of Presentation
      東京
    • Related Report
      2013 Annual Research Report
    • Invited
  • [Book] 確率的最適化(機械学習プロフェッショナルシリーズ)2015

    • Author(s)
      鈴木大慈
    • Total Pages
      176
    • Publisher
      講談社
    • Related Report
      2015 Annual Research Report
  • [Book] ビッグデータ・マネジメント-データサイエンティストのためのデータ利活用技術と事例2013

    • Author(s)
      嶋田茂,伊藤大雄,坂本 比呂志,當仲寛哲,鷲尾隆,上田修功,杉山将,鹿島久嗣,鈴木大慈,河原大輔,黒橋禎夫,関根聡,西尾信彦,稲越宏弥,ほか計36名
    • Total Pages
      329
    • Publisher
      株式会社エヌ・ティー・エス
    • Related Report
      2013 Annual Research Report
  • [Remarks]

    • URL

      http://www.ism.ac.jp/~fukumizu/

    • Related Report
      2017 Annual Research Report
  • [Remarks] http://www.ism.ac.jp/~fukumizu/

    • Related Report
      2016 Annual Research Report
  • [Remarks]

    • URL

      http://www.ism.ac.jp/~fukumizu/

    • Related Report
      2015 Annual Research Report
  • [Remarks] 「スパースモデリングの深化と高次元データ駆動科学の創成」セミパラメトリックベイズ班

    • URL

      http://sparse-modeling.jp/program/C01-2.html

    • Related Report
      2014 Annual Research Report
  • [Remarks] Kenji Fukumizu's Home Page

    • URL

      http://www.ism.ac.jp/~fukumizu/

    • Related Report
      2013 Annual Research Report
  • [Remarks] スパースモデリングの深化と高次元データ駆動科学の創成

    • URL

      http://sparse-modeling.jp/

    • Related Report
      2013 Annual Research Report
  • [Funded Workshop] Workshop on Functional Inference and Machine Intelligence (FIMI)2018

    • Related Report
      2017 Annual Research Report

URL: 

Published: 2013-07-10   Modified: 2022-03-29  

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