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A study on optimizing graphs for machine learning algorithms

Research Project

Project/Area Number 24800036
Research Category

Grant-in-Aid for Research Activity Start-up

Allocation TypeSingle-year Grants
Research Field Intelligent informatics
Research InstitutionKyoto University

Principal Investigator

KARASUYAMA Masayuki  京都大学, 化学研究所, 助教 (40628640)

Project Period (FY) 2012-08-31 – 2014-03-31
Project Status Completed (Fiscal Year 2013)
Budget Amount *help
¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords機械学習 / グラフ / バイオインフォマティクス / 半教師付き学習
Research Abstract

A variety types of network data have been attracted wide attention, such as protein interaction network in biology and link relationships in social networks. This research has studied statistical algorithms to analyze these network data, which can be represented as ``graph'', and developed highly accurate methods for prediction problem on graphs compared to existing approaches.

Report

(3 results)
  • 2013 Annual Research Report   Final Research Report ( PDF )
  • 2012 Annual Research Report
  • Research Products

    (7 results)

All 2013 2012

All Journal Article (1 results) (of which Peer Reviewed: 1 results) Presentation (6 results)

  • [Journal Article] Multiple Graph Label Propagation by Sparse Integration2013

    • Author(s)
      Karasuyama, M. and Mamitsuka, H.
    • Journal Title

      IEEE Transactions on Neural Networks and Learning Systems

      Volume: 24 Issue: 12 Pages: 1999-2012

    • DOI

      10.1109/tnnls.2013.2271327

    • Related Report
      2013 Annual Research Report 2013 Final Research Report
    • Peer Reviewed
  • [Presentation] Manifold-based Similarity Adaptation for Label Propagation2013

    • Author(s)
      M Karasuyama, and H Mamitsuka
    • Organizer
      Advances in Neural Information Processing Systems (NIPS)
    • Related Report
      2013 Final Research Report
  • [Presentation] 局所線形近似に基づくラベル伝播のための類似度適合2013

    • Author(s)
      烏山昌幸, 馬見塚拓
    • Organizer
      情報論的学習理論と機械学習研究会 (IBISML)
    • Related Report
      2013 Final Research Report
  • [Presentation] Manifold-based Similarity Adaptation for Label Propagation2013

    • Author(s)
      M. Karasuyama and H. Mamitsuka
    • Organizer
      Neural Information Processing Systems
    • Place of Presentation
      Lake Taho, Nevada, US
    • Related Report
      2013 Annual Research Report
  • [Presentation] 局所線形近似に基づくラベル伝播のための類似度適合2013

    • Author(s)
      烏山昌幸
    • Organizer
      情報論的学習理論と機械学習研究会
    • Place of Presentation
      名古屋工業大学
    • Related Report
      2012 Annual Research Report
  • [Presentation] ラベル伝播アルゴリズムにおける複数グラフのスパース結合法2012

    • Author(s)
      烏山昌幸, 馬見塚拓
    • Organizer
      情報論的学習理論と機械学習研究会 (IBISML)
    • Related Report
      2013 Final Research Report
  • [Presentation] ラベル伝播アルゴリズムにおける複数グラフのスパース結合法2012

    • Author(s)
      烏山昌幸
    • Organizer
      第15回情報論的学習理論ワークショップ
    • Place of Presentation
      筑波大学 東京キャンパス文京校舎
    • Related Report
      2012 Annual Research Report

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Published: 2012-11-27   Modified: 2019-07-29  

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