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J-GLOBAL ID:200901011658930737   Update date: Feb. 22, 2024

Ichino Manabu

イチノ マナブ | Ichino Manabu
Affiliation and department:
Research field  (2): Intelligent informatics ,  Information theory
Research keywords  (5): Symbolic Data Analysis ,  Pattern recognition ,  Data mining ,  Knowledge discovery ,  Neighborhood graph
Research theme for competitive and other funds  (10):
  • 2013 - 2017 The quantile methods for symbolic data analysis
  • 2010 - 2013 The quantile methods for symbolic data analysis
  • 2007 - 2010 Detection of covariant relations in multidimensional data
  • 2004 - 2006 Symbolic data analysis based on the relative neighborhood graphs
  • 2002 - 2004 Symbolic data analysis based on the relative neighborhood graphs
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Papers (15):
  • Manabu Ichino. Exploratory Analysis of Distributional Data Using the Quantile Method. AppliedMath. 2024. 4. 1. 261-288
  • Manabu Ichino. The Lookup Table Regression Model for Histogram-Valued Symbolic Data. Stats. 2022. 2022. 5. 1271-1293
  • M Ichino, K Umbleja, H Yaguchi. Unsupervised feature selection for histogram-valued symbolic data using hierarchical conceptual clustering. Stats. 2021. 4. 2. 359-384
  • K Umbleja, M Ichino H Yaguchi. Hierarchical conceptual clustering based on quantile method for identifying microscopic details in distributional data. Advances in Data Analysis and Classification. 2021. 15. 2. 407-436
  • K Umbleja, M Ichino, H Yaguchi. Improving symbolic data visualization for pattern recognition and knowledge discovery. Visual Informatics. 2020. 4. 1. 23-31
more...
MISC (96):
  • Manabu Ichino, Kadri Umbleja. Similarity and dissimilarity measures for mixed feature-type symbolic data. Springer Proceedings in Mathematics and Statistics. 2018. 227. 131-144
  • M. Ichino and P. Brito, A hierarchical conceptual clustering based on the quantile method for mixed feature-type data, Invited Paper Sessions (IPS 079) at the 59th World Statistics Congress of the International Statistical Institute held in Hong Kong, ・・・. 2013
  • M.Ichino and P. Brito, The data accumulation PCA to analyze periodically summarized multiple data tables, COMSTAT 2012, Limassol, Cyprus. 2012
  • P. Brito and M. Ichino, Conceptual clustering of symbolic data using quantile representations approaches, 4th International Conference of the ERCIM WG on Computing & Statistics, London. 2011
  • A. Nagoya, Y. Ono, and M. Ichino, A generalized measure of covariant relations based on relative neighborhood relations, Far East Journal of Theoretical Statistics. 2011
more...
Lectures and oral presentations  (11):
  • 鎖状構造抽出に有効な特徴選択法の高速化
    (電子情報通信学会研究会 2010)
  • サンプルの隣接関係に着目した多次元データに内在する共変関係 検出に関する考察,
    (情報処理学会第67回全国大会, 2005)
  • 関東周辺既存大学の分析,
    (日本教育情報学会, 2004)
  • 相関係数の一般化に関する研究,
    (第64回情報処理学会全国大 会, データベースとメディア, 一般講演, マルチメディア解析と特徴分析, 2002)
  • Generality ordered relative neighborhood graph を用いた特徴選択,
    (デー タベースとメディア, 一般講演, マルチメディア解析と特徴分析, 2002)
more...
Works (2):
  • NPO法人アートバーブズフォーラム理事
    2008 - 現在
  • International Openair Expressions
    2002 - 現在
Education (2):
  • 1967 - 1973 Tokyo Denki University Graduate School of Engineering
  • 1963 - 1967 Tokyo Denki University School of Engineering Department of Electronic Engineering
Professional career (1):
  • Doctor of Engineering (Tokyo Denki University)
Work history (9):
  • 2014/04 - 現在 Tokyo Denki University Professor Emeritus
  • 2007/04 - 2014/03 Tokyo Denki University Division of Information System Design School of Science and Engineering Professor
  • 2000/04 - 2007/03 Tokyo Denki University Professor, Department of Information and Arts, School of Science and Engineering
  • 1984/04 - 2000/03 Tokyo Denki University Professor, Department of Computers and Systems Engineering, School of Science and Engineering
  • 1976/03 - 1984/03 Tokyo Denki University Associate Professor, School of Science and Engineering
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Committee career (4):
  • 2004 - 2007 理事
  • 2001 - 2007 評議員
  • 1998 - 2001 理事
  • 1993 - 1997 理工学部長,理事
Association Membership(s) (7):
日本分類学会 ,  人工知能学会 ,  情報処理学会 ,  電子情報通信学会 ,  Classification Society of North America ,  Pattern Recognition Society ,  IEEE
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