Consolidation of Visualization Platform Toward Facilitating Sparse Modeling

2017 Fiscal Year Final Research Report

• Project Area: Initiative for High-Dimensional Data-Driven Science through Deepening of Sparse Modeling
• Project/Area Number: 25120014
• Research Category: Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
• Allocation Type: Single-year Grants
• Review Section: Complex systems
• Research Institution: Keio University
• Principal Investigator: Fujishiro Issei 慶應義塾大学, 理工学部(矢上), 教授 (00181347)
• Co-Investigator(Kenkyū-buntansha): 渡辺 一帆 豊橋技術科学大学, 工学(系)研究科(研究院), 講師 (10506744) ; 高橋 成雄 会津大学, コンピュータ理工学部, 教授 (40292619)
• Research Collaborator: WU Hsiang-Yun ウィーン工科大学, ビジュアルコンピューティングと人間中心技術研究所, 研究員
• Project Period (FY): 2013-06-28 – 2018-03-31
• Keywords: 可視化 / スパースモデリング / 機械学習 / トポロジー

Outline of Final Research Achievements

The goal of this project is to build a visualization platform for understanding the behavior of a given high-dimensional data in physical space by projecting it onto a designated information space. For this purpose, we transform relatively low-dimensional data obtained through sparse modeling to 2, 3, or 4-dimensional space where we can fully visualize the characteristics of the original high-dimensional data. The idea behind the project is to establish an interactive model called human-in-the-loop by incorporating visual feedback from the users in the analysis of high-dimensional data based on sparse modeling.

Free Research Field

情報学