KARASUYAMA Masayuki

写真a

Affiliation Department etc.

Department of Computer Science
Department of Computer Science

Title

Associate Professor

Graduating School

  •  
    -
    2006.03

    Nagoya Institute of Technology   Faculty of Engineering   Department of Computer Science   Graduated

Graduate School

  •  
    -
    2011.03

    Nagoya Institute of Technology  Graduate School, Division of Engineering  Scientific and Engineering SimulationDoctor's Course  Completed

  •  
    -
    2008.03

    Nagoya Institute of Technology  Graduate School, Division of Engineering  Scientific and Engineering SimulationMaster's Course  Completed

External Career

  • 2015.12
    -
    2019.03

      Researcher  

  • 2015
    -
    2020.03

      Researcher  

  • 2012.01
    -
    2015.03

    Kyoto University   Intitute for Chemical Research, Bioinformatics Center   Assistant Professor  

  • 2011.04
    -
    2011.12

    Tokyo Institute of Technology   Special researcher of the Japan Society for the Promotion of Science  

 

Papers

  • Distance Metric Learning for Graph Structured Data

    T. Yoshida, I. Takeuchi, and M. Karasuyama

    Machine Learning     2021.06  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

  • Exploration of natural red-shifted rhodopsins using a machine learning-based Bayesian experimental design

    K. Inoue, M. Karasuyama, R. Nakamura, M Konno, D. Yamada, K. Mannen, T. Nagata, Y. Inatsu, H. Yawo, K. Yura, O. Béjà, H. Kandori, and I. Takeuchi

    Communications Biology     2021.03  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

  • Efficient Experimental Search for Discovering a Fast Li-Ion Conductor from a Perovskite-Type LixLa(1-x)/3NbO3 (LLNO) Solid-State Electrolyte Using Bayesian Optimization

    Z. Yang, S. Suzuki, N. Tanibata, H. Takeda, M. Nakayama, M. Karasuyama, and I. Takeuchi

    Journal of Physical Chemistry C     2021  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

  • Stat-DSM: Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction

    V. N. L. Duy, T. Sakuma, T. Ishiyama, H. Toda, K. Arai, M. Karasuyama, Y. Okubo, M. Sunaga, H. Hanada, Y. Tabei, I. Takeuchi

    IEEE Transactions on Knowledge and Data Engineering     2020  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

  • Prediction of formation energies of large-scale disordered systems via active-learning based executions of ab initio local-energy calculations: A case study on a Fe random grain boundary model with millions of atoms

    T. Tamura, M. Karasuyama

    Physical Review Materials     2020  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

  • Multi-objective Bayesian Optimization using Pareto-frontier Entropy

    S. Suzuki, S. Takeno, T. Tamura, K. Shitara, M. Karasuyama

    Proceedings of The 37th International Conference on Machine Learning (ICML 2020)     2020  [Refereed]

    Research paper (international conference proceedings)   Multiple Authorship

  • Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization

    S. Takeno, H. Fukuoka, Y. Tsukada, T. Koyama, M. Shiga, I. Takeuchi, M. Karasuyama

    Proceedings of The 37th International Conference on Machine Learning (ICML 2020)     2020  [Refereed]

    Research paper (international conference proceedings)   Multiple Authorship

  • Bayesian-optimization-guided experimental search of NASICON-type solid electrolytes for all-solid-state Li-ion batteries

    M. Harada, H. Takeda, S. Suzuki, K. Nakano, N. Tanibata, M. Nakayama, M. Karasuyama,, I. Takeuchi

    Journal of Materials Chemistry A     2020  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

  • Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling

    S. Takeno, Y. Tsukada, H. Fukuoka, T. Koyama, M. Shiga, M. Karasuyama

    Physical Review Materials     2020  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

  • Active Learning for Level Set Estimation Under Input Uncertainty and its Extensions

    Y. Inatsu, M. Karasuyama, K. Inoue, I. Takeuchi

    Neural Computation     2020  [Refereed]

    Research paper (scientific journal)   Multiple Authorship

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Books

  • Big Data Analytics in Genomics

    K.-C. Wong (ed.), S. Yotsukura, M. Karasuyama, I. Takigawa, H. Mamitsuka, et al. (Part: Allotment Writing ,  A Bioinformatics Approach for Understanding Genotype-Phenotype Correlation in Breast Cancer (chapter13) )

    Springer  2016.11

Presentations

  • 属性区間付きグラフを用いた予測グラフマイニング

    朝日陽向, 烏山昌幸

    情報論的学習理論と機械学習研究会(IBISML)  2021.06  -  2021.06 

  • Max-value Entropy Searchに基づくMulti-fidelityベイズ最適化

    竹野思温, 福岡準史, 塚田祐貴, 小山敏幸, 志賀元紀, 竹内一郎, 烏山昌幸

    第22回情報論的学習理論ワークショップ (IBIS2019)  2019.11  -  2019.11 

  • Cost-sensitive Bayesian optimization for multiple objectives and its application to material science

    2017.06  -  2017.06 

  • Statistical Prediction of Grain-Boundary Properties

    T. Tamura, R. Arakawa, M. Karasuyama, R. Kobayashi, S. Ogata

    The 9th Pacific Rim International Conference of Advanced Materials and Processing  2016.08  -  2016.08 

  • Statistical Prediction of Grain-boundary Properties

    T. Tamura, R. Arakawa, M. Karasuyama, R. Kobayashi, S. Ogata

    The third International Symposium on Atomistic Modeling for Mechanics and Multiphysics of Materials  2016.06  -  2016.06 

  • Regularization Path of Cross-Validation Error Lower Bounds

    A. Shibagaki, Y. Suzuki, M. Karasuyama, I. Takeuchi

    Advances in Neural Information Processing Systems (NIPS)  2015.12  -  2015.12 

  • Manifold-based Similarity Adaptation for Label Propagation

    M. Karasuyama, H. Mamitsuka

    Advances in Neural Information Processing Systems (NIPS)   2013  -  2013 

  • Suboptimal Solution Path Algorithm for Support Vector Machine

    M. Karasuyama, I. Takeuchi

    International Conference on Machine Learning (ICML)  2011  -  2011 

  • Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines

    M. Karasuyama, N. Harada, M. Sugiyama, I. Takeuchi

    IEEE International Workshop on Machine Learning for Signal Processing (MLSP)  2011  -  2011 

  • Nonlinear Regularization Path for the Modified Huber loss Support Vector Machines

    M. Karasuyama, I. Takeuchi

    International Joint Conference on Neural Networks (IJCNN)  2010  -  2010 

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