Research keywords (4)：
High Dimensional Data Analysis
, Machine Learning
, reduction of hubness
, Natural Language Processing
Research theme for competitive and other funds (6)：
2021 - 2026 単語分散表現の頻度エンコード問題の解消
2021 - 2025 「ハブネス」を活用して行う高次元データの解析
2016 - 2020 Elucidation of hub phenomenon occurring in large-scale data and its application to bio-medical data
2016 - 2020 Hubness Analysis
2013 - 2016 Similarity Measures for Nearest Neighbor Search and Classification Methods in High Dimensional and Large Number of Data
2012 - 2016 Studies on link analytic similarity measures for high-dimensional/structured data
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Papers (22)：
Tomoya Sasaki, Yuto Kikuchi, Kazuo Hara, Ikumi Suzuki. Investigating Word Vectors for the Negation of Verbs. SN Comput. Sci. 2024. 5. 2. 222-222
Toshiki Yamaguchi, Kazuo Hara, Ikumi Suzuki. Robust Method to Convert HIRAGANA Sequences into Japanese Text. 2021 IEEE International Conference on Big Data (Big Data). 2021. 6058-6060
Tomoya Sasaki, Arisa Nakamura, Jun-Ichi Harasawa, Kazuo Hara, Ikumi Suzuki, Tatsuhiro Takahashi. Bayesian Optimization With an Auxiliary Classifier for the Development of Polymer Materials. 2021 IEEE International Conference on Big Data (Big Data). 2021. 6014-6016
Hiroki Tomori, Tomohiro Koyama, Hiromitsu Nishikata, Akinori Hayasaka, Ikumi Suzuki. Developing a Flexible Segment Unit for Redundant-DOF Manipulator Using Bending Type Pneumatic Artificial Muscle. ROMANSY 23 - Robot Design, Dynamics and Control. 2021. 272-279
鈴木 郁美. 少数サンプルと高次元データへの確率とグラフに基づくアプローチ(機械学習・データマイニング,<特集>人工知能分野における博士論文). 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence. 2013. 28. 1. 158-158
