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J-GLOBAL ID：201501037290625048   Update date: Feb. 01, 2024

Sakata Ayaka

サカタ アヤカ | Sakata Ayaka
Affiliation and department：
The Institute of Statistical Mathematics Department of Statistical Inference & Mathematics/Research Center for Statistical Machine Learning

About The Institute of Statistical Mathematics Department of Statistical Inference & Mathematics/Research Center for Statistical Machine Learning


Job title： Associate Professor
Homepage URL  (1)： http://www.ism.ac.jp/~ayaka/
Research field  (2)： Mathematical physics and basic theory ,  Soft computing
Research keywords  (4)： Statistical Physics ,  Statistical Science ,  Statistical Machine Learning ,  Evolutional biology
Research theme for competitive and other funds  (11)：
  • 2023 - 2027 確率的推論によるデータ取得とデータ解析の包括的最適化
  • 2022 - 2027 Statistical mechanics approach to high-dimensional machine learning
  • 2020 - 2024 大自由度生命システムの次元縮減:検証、理論化、生物状態論及び神経系学習への展開
  • 2019 - 2023 求解軌道のマクロ表現によるアルゴリズム制御理論の創出
  • 2019 - 2022 階層モデルにおけるベイズ的スパース推定に対するモデル選択理論の構成
Show all
Papers (26)：
  • Ayaka Sakata, Kunihiko Kaneko. Evolutionary Shaping of Low-Dimensional Path Facilitates Robust and Plastic Switching Between Phenotypes. Physical Review Research. 2023. 5. 4. 043296
  • Ayaka Sakata, Yoshiyuki Kabashima. Decision Theoretic Cutoff and ROC Analysis for Bayesian Optimal Group Testing. IEEE Transactions on Information Theory. 2023. 69. 9. 5902-5920
  • Ayaka Sakata. Prediction errors for penalized regressions based on generalized approximate message passing. Journal of Physics A: Mathematical and Theoretical. 2023
  • 坂田綾香, 樺島祥介. ベイズ的グループテストのカットオフ値評価とROC解析. 統計数理. 2022. 70. 1. 89-114
  • Ayaka Sakata, Tomoyuki Obuchi. Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control. Journal of Statistical Mechanics: Theory and Experiment. 2021. 2021. 9. 093401-093401
ｍore...
MISC (23)：
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Lectures and oral presentations  (30)：
  • グラフィカルモデルを用いた確率推論の回帰問題における展開
    (2023)
  • Evolutional Construction of Stable Expression and Switching Paths for Multiple Phenotypes
    (9IDMRCS 2023)
  • Statistical Physics Insights on Learning Gaussian Bayesian Networks with Incomplete Data
    (Statphys 28 2023)
  • Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control
    (2023)
  • Exploring the Intersection of Physics, Information Science, Statistics, and Biophysics: My Research Journey
    (Bristol Women's day 2023)
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Education (1)：
  • - 2011 The University of Tokyo Graduate School of Arts and Sciences Basic Science,Section of Multi-Disciplinary Sciences,
Professional career (1)：
  • Ph.D. (The University of Tokyo)
Work history (5)：
  • 2020/04 - 現在 The Institute of Statistical Mathematics Associate Professor
  • 2015/04 - 2020/03 The Institute of Statistical Mathematics Assistant Professor
  • 2014/04 - 2015/03 RIKEN Special PostDoctoral Researcher
  • 2011/04 - 2014/03 Tokyo Institute of Technology Department of Computational Intelligence and Systems Science JSPS Research Fellow (PD)
  • 2008/04 - 2011/03 University of Tokyo Graduate school of Arts and Sciences JSPS Research Fellow (DC1)
Committee career (2)：
  • 2021 - Japanese Journal of Statistics and Data Science編集委員
  • 2016/10 - 2017/09 日本物理学会 領域11運営委員
Awards (5)：
  • 2019/04 - Ministry of Education, Culture, Sports, Science and Technology The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology, The Young Scientists’ Prize Statistical Machine Learning based on spin-glass theory
  • 2017/11 - IBIS2017 Presentation Award Message Passing for nonconvex sparse penalties and its convergence condition
  • 2017/06 - Shiseido Female Researcher Science Grant
  • 2014/12 - SITA Awards
  • 2012/11 - IBIS2012 Poster Awards
Association Membership(s) (3)：
THE JAPAN STATISTICAL SOCIETY ,  THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS ,  THE PHYSICAL SOCIETY OF JAPAN
※ Researcher’s information displayed in J-GLOBAL is based on the information registered in researchmap. For details, see here.

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