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Establishment of Self-information Control Mechanism for Machine Learning

Research Project

Project/Area Number 25540094
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeMulti-year Fund
Research Field Intelligent informatics
Research InstitutionUniversity of Tsukuba

Principal Investigator

SAKUMA Jun  筑波大学, システム情報系, 准教授 (90376963)

Co-Investigator(Kenkyū-buntansha) KAMISHIMA Toshihiro  産業技術総合研究所, ヒューマンライフテクノロジー研究部門, 研究員 (50356820)
Project Period (FY) 2013-04-01 – 2015-03-31
Project Status Completed (Fiscal Year 2014)
Budget Amount *help
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2013: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Keywordsプライバシー / 機械学習 / データマイニング / セキュリティ / 中立化 / 差別配慮 / 自己情報コントロール / 匿名化 / プライバシ
Outline of Final Research Achievements

The neutrality of predictions made by machine learning is measured by dependency between values of a specified attribute and predictions. In this research, we developed a framework that controls dependency between prediction and a specified attribute values to achieve fairness, privacy protection, and prevention of discrimination of predictions. One of the significant results of our study is the generalization analysis of neutrality, in which we proved that generalization neutrality can be probabilistically upper-bounded by O(1/√n) for unseen examples.

Report

(3 results)
  • 2014 Annual Research Report   Final Research Report ( PDF )
  • 2013 Research-status Report
  • Research Products

    (4 results)

All 2014 2013 Other

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (2 results)

  • [Journal Article] Neutralized Empirical Risk Minimization with Generalization Neutrality Bound2014

    • Author(s)
      Kazuto Fukuchi, Jun Sakuma
    • Journal Title

      The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2014

      Volume: 1 Pages: 21-30

    • DOI

      10.1007/978-3-662-44848-9_27

    • ISBN
      9783662448472, 9783662448489
    • Related Report
      2014 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Efficiency Improvement of Neutrality-Enhanced Recommendation2013

    • Author(s)
      Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, and Jun Sakuma
    • Journal Title

      Recsys'13, Human Decision Making

      Volume: Workshop Proceedings Pages: 1-8

    • Related Report
      2013 Research-status Report
    • Peer Reviewed
  • [Presentation] Correcting Popularity Bias by Enhancing Recommendation Neutrality.2014

    • Author(s)
      Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Jun Sakuma
    • Organizer
      Poster Proceedings of the 8th ACM Conference on Recommender Systems, RecSys 2014
    • Place of Presentation
      the Crowne Plaza hotel, Foster City, Silicon Valley, CA, USA
    • Year and Date
      2014-10-06 – 2014-10-10
    • Related Report
      2014 Annual Research Report
  • [Presentation] 匿名化データからのロバスト線形回帰とその汎化誤差解析

    • Author(s)
      小林星平, 佐久間 淳
    • Organizer
      2014年暗号と情報セキュリティシンポジウム(SCIS2014)
    • Place of Presentation
      鹿児島
    • Related Report
      2013 Research-status Report

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Published: 2014-07-25   Modified: 2019-07-29  

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