2023年度

学術論文・国際会議論文（査読付）
    [小澤研]
  1. Le Trieu PHONG, Tran Thi PHUONG, Lihua WANG, Seiichi OZAWA, “Frameworks for Privacy-Preserving Federated Learning,” IEICE Transactions on Information and Systems, 2024, Vol. E107.D, Issue 1, pp. 2-12, January 01, 2024.
  2. Septiviana Savitri Asrori, Lihua Wang, and Seiichi Ozawa, “Permissioned Blockchain-Based XGBoost for Multi Banks Fraud Detection,” In: Tanveer, M., Agarwal, S., Ozawa, S., Ekbal, A., Jatowt, A. (eds) Neural Information Processing. ICONIP 2022. Lecture Notes in Computer Science, vol 13625. Springer, Cham, pp. 683–692, 2013.
  3. Enna Hirata, Takahiro Yamashita, and Seiichi Ozawa, “Researcher Network Visualization Using Matrix Researcher2vec,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.27, No.4, pp. 603-608, 2023.
  4. Muhammad Fakhrur Rozi, Tao Ban, Seiichi Ozawa, Akira Yamada, Takeshi Takahashi, Sangwook Kim, and Daisuke Inoue. “Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation.” in IEEE Access. vol. 11. pages 102727-102745. 2023.
    [大森研]
  1. Toshiaki Omori, Shoi Suzuki, Katsuyoshi Michibayashi and Atsushi Okamoto, “Super-resolution of X-ray CT Images of Rock Samples by Sparse Representation: Applications to the Complex Texture of Serpentinite”, Scientific Reports(Nature Publishing Group), Vol. 13, pp. 6648: 1-11 (2023)
  2. Taketo Omi, and Toshiaki Omori, “Sequential Monte Carlo Framework for Simultaneously Estimating and Controlling Nonlinear Neuronal Dynamics”, Proceedings of 2023 International Symposium on Nonlinear Theory and Its Applications, in press. (2023)
  3. Hirozo Nakano, Amitava Majumdar, and Toshiaki Omori, “Data-Driven Estimation of Spatial Electrical Property of Multi-Compartment Neuron Models by Replica Exchange Monte Carlo Method”, Proceedings of 2023 International Symposium on Nonlinear Theory and Its Applications, in press. (2023)
  4. Shoi Suzuki, Atsushi Okamoto, Katsuyoshi Michibayashi, and Toshiaki Omori, “Three-dimensional Super-resolution of X-ray CT Data of Rock Samples by Sparse Representation Learning”, ACM International Conference Proceeding Series, in press. (2023)
  5. Hirozo Nakano, Toshiaki Omori, “Estimating of Spatial Input Currents in Morphological Neuron Models by Data-driven Approach”, Proceedings of the Twenty-Ninth International Symposium on Artificial Life and Robotics, pp. 474-479 (2024)
  6. Tsubasa Shoji and Toshiaki Omori, “Data-driven Estimation of Neuronal Network Structure with Biologically Plausible Connectivity Prior”, Proceedings of the Twenty-Ninth International Symposium on Artificial Life and Robotics, pp. 470-473 (2024)
  7. Yuya Note, Toshiaki Omori “Transforming Neural Ordinary Differential Equations into Interpretable Sparse Expressions via Identification of Nonlinear Dynamics under General Dynamical Constraints” Proceedings of the Twenty-Ninth International Symposium on Artificial Life and Robotics, pp. 466-469 (2024)
  8. Yuya Note, Takaharu Yaguchi, and Toshiaki Omori, “Sparse Estimation of Dynamical System Based on Hamiltonian Mechanics”, Proceedings of 3rd Annual AAAI Workshop on AI to Accelerate Science and Engineering, p. 1-4 (2024)
  9. Yuya Note, Takaharu Yaguchi, Toshiaki Omori, “Sparse Representation of Koopman Operator”, Proceedings of International Conference on Scientific Computing and Machine Learning 2024 (2024)
国際会議発表
    [小澤研]
  1. Takeshi Urade, Nobuaki Yamasaki, Junichiro Hirata, Yasuyoshi Okamura, Munenori Uemura, Kaito Nanchi, Tatsuya Hattori, Yuki Mitani, Yasuo Chihara, Kiyoyuki Chinzei, Seiichi Ozawa, Masato Fujisawa, and Takumi Fukumoto, “Surgical education from robot-assisted surgery training skills at first touch”, EAES2023, 20-23 June, 2023.
    [大森研]
  1. Toshiaki Omori, Hiroaki Inoue, and Koji Hukushima, “Data-driven Method for Estimating Nonlinear Dynamics by Replica Exchange Particle Markov Chain Monte Carlo Method”, 28th IUPAP International Conference on Statistical Physics (2023)
  2. Taketo Omi and Toshiaki Omori, “Data-driven Framework for Simultaneously Estimating and Controlling Neuronal Nonlinear Dynamics”, 28th IUPAP International Conference on Statistical Physics (2023)
  3. Toshiaki Omori, Hiroaki Inoue, and Koji Hukushima, “Data-driven Estimation of Nonlinear Dynamical Systems by Replica Exchange Particle Markov Chain Monte Carlo Method”, 34th IUPAP Conference on Computational Physics (2023)
  4. Taketo Omi and Toshiaki Omori, “Simultaneous Estimation and Control Framework for Neuronal Dynamics Based on Statistical Machine Learning Approach”, 34th IUPAP Conference on Computational Physics (2023)
  5. Hirozo Nakano, Amitava Majumdar, and Toshiaki Omori, “Extracting Spatiotemporal Dynamics of Neural Systems by Computational and Data-driven Approaches”, 34th IUPAP Conference on Computational Physics (2023)
  6. Toshiaki Omori, Shoi Suzuki, Katsuyoshi Michibayashi, and Atsushi Okamoto, “Super-resolution of X-ray CT Images of Rock Samples by Sparse Representation: Applications to the Complex Texture of Serpentinite”, 17th International Symposium on Water-Rock Interaction and the 14th International Symposium on Applied Isotope Geochemistry (2023)
  7. Takuma Ihara and Toshiaki Omori, “Data driven Framework for Estimating Nonlinear Neural Dynamics Based on Nonuniform Sparse Modeling”, 7th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (2023)
  8. Kensuke Inaba and Toshiaki Omori, “Visualizing Process of Image Reconstruction from Brain Activities by Using Nonparametric Generative Model”, 7th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (2023)
  9. Hirozo Nakano, Toshiaki Omori, “Data-driven Estimation Framework for Extracting Nonlinear Dynamics in Biophysical Neuron Models” The 12th RIEC International Symposium on Brain Functions and Brain Computer (2024)
  10. Tsubasa Shoji, Toshiaki Omori, “Machine Learning Algorithm for Estimating Neuronal Network Structure with Biologically Plausible Connectivity Prior” The 12th RIEC International Symposium on Brain Functions and Brain Computer (2024)
  11. Taketo Omi, Toshiaki Omori “Data-driven Online Framework for Estimation and Feedback Control of Neuronal Dynamics by Fully Sequential Monte Carlo Method” The 12th RIEC International Symposium on Brain Functions and Brain Computer (2024)
  12. Koki Fujiwara, Toshiaki Omori “Parameter Estimation of Neuron-glia Interactive Dynamics with Multiple Time Scales” The 12th RIEC International Symposium on Brain Functions and Brain Computer (2024)
  13. Tomu Watanabe, Toshiaki Omori “Data-driven Method for Extracting Latent Neuronal Systems from Imaging Data” The 12th RIEC International Symposium on Brain Functions and Brain Computer (2024)
国内学会発表/シンポジウム
    [小澤研]
  1. 三宅健太，小澤誠一，福田　純，福井　航，平田一郎、”深層学習を用いた画像の回帰問題に対する判断根拠可視化手法の開発”, 情報処理学会第86回全国大会, 2024年3月16日
  2. 北野優斗、王　立華、小澤誠一、”継続学習型連合学習モデルにおける効率的なリプレイデータの選択”、信学技報, vol. 123, no. 424, ISEC2023-95, pp. 135-141, 2024年3月13日
  3. 宮武 和咲、遠藤 由紀子、山田 明、班 涛、高橋 健志、小澤 誠一、”アクティブスキャンによるIoTデバイスフィンガープリントを利用したマルウェア感染端末数の推定”、2024年暗号と情報セキュリティシンポジウム（SCIS2024) 論文集、8ページ、2024年1月25日
  4. 中野 瑠人、山田 明、班 涛、高橋 健志、小澤 誠一、”Cloak-Bench：大規模言語モデルによるセキュリティ分析の定量的評価方式 – フィッシングキットのクローキング検出への応用”、2024年　暗号と情報セキュリティシンポジウム（SCIS2024) 論文集、8ページ、2024年1月24日
  5. 鍛冶佳佑, 中野瑠人, 山田 明, 小澤 誠一, “大規模言語モデルによるセキュリティ対策の視覚認知メカニズムのモデル化に向けた検討,” コンピュータセキュリティシンポジウム 2023論文集，pp. 1536-1543, 2023年11月2日
  6. 小杉樹来, 小澤誠一, 廣瀬勇秀, 池田佳弘, 中川憲保, 飯塚正昭, 西田大輔, “ChatGPTを用いたニュース記事のESGトピック分析,” 第31回人工知能学会金融情報学研究会（SIG-FIN）, SIG-FIN-031-08, pp. 36-41, 2023年10月14日
  7. 高須 悠一朗、小澤 誠一、廣瀬 勇秀、池田 佳弘、中川 憲保、飯塚 正昭、西田 大輔, “対照学習済みBERTによる不祥事記事分類と文章埋め込み表現の考察”, 人工知能学会全国大会論文集, 2023年6月8日,https://doi.org/10.11517/pjsai.JSAI2023.0_3M1GS1002
    [大森研]
  1. Shoi Suzuki, Atsushi Okamoto, Katsuyoshi Michibayashi, and Toshiaki Omori, “Data-Driven Super-Resolution for Rock Sample CT Images Based on Sparse Modeling: Applications to the Complex Texture of Serpentinite”, Japan Geoscience Union Meeting 2023, 2023年
  2. 大森敏明，神経システム制御へのデータ駆動型アプローチ，定量生物学の回第十一回年会 (2024)
解説・技術報告/紀要
招待講演・セミナー
    [小澤研]
  1. 小澤 誠一、「組織間連合学習AIによる社会課題へのチャレンジ – 銀行不正送金検知の取組み」、NICTサイバーセキュリティシンポジウム2024、2024年2月16日
  2. 小澤誠一, “AIによる特殊詐欺監視,” 2023年度日本OR学会関西支部シンポジウム, 2023年12月20日
  3. 小澤 誠一, 大塚 玲, 菅 和聖, 大貫秀明, “[座談会] AIセキュリティの論点”, 人工知能学会 合同研究会2023, 第2回 安全性とセキュリティ研究会 (SIG-SEC), 2023年11月24日
  4. Irwin King (Moderator), Jonathan H. Chan, Kenji Doya, Włodzisław Duch, Seiichi Ozawa (Panelists), “The Impact of Professional Societies in Shaping Disruptive Technologies such as Generative AI,” The 2023 International Conference on Neural Information Processing (ICONIP2023), November 21, 2023.
  5. Seiichi Ozawa, “eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees and Challenges to Bank Fraud Detection for Anti-Money Laundering,” CIC-NICT Workshop, Canadian Institute for Cybersecurity, University of New Brunswick, 15 September, 2023.
  6. Seiichi Ozawa, “eFL-Boost: Efficient Federated Learning for Gradient Boosting Decision Trees and Challenges to Bank Fraud Detection for Anti-Money Laundering,” Workshop on Cyber Defense and Resilience at Behaviour-Centric Cybersecurity Center (BCCC), York University, 25 September, 2023.
  7. Seiichi Ozawa, “Privacy-Preserving Machine Learning for Big Data Analysis – How can we solve social issues using AI? -,” Chitose International Forum on Science & Technology 2023, September 29, 2023.
  8. 小澤 誠一, “データサイエンスと活用事例 〜深層学習を用いた大豆の生育情報センシング〜”, 兵庫県立農林水産技術総合センター講演, 2023年8月31日
    [大森研]
  1. 大森敏明，データ駆動型アプローチに基づく非線形ダイナミクスの推定，情報計測オンラインセミナーシリーズ－数理・情報科学×計測科学の高度融合による新展開－(2024)
受賞
    [小澤研]
  1. 鍛冶佳佑, 中野瑠人, 山田 明, 小澤 誠一, CSS2023奨励賞, 情報処理学会，「大規模言語モデルによるセキュリティ対策の視覚認知メカニズムのモデル化に向けた検討」, 2023年10月30日
    [大森研]
  1. Takuma Ihara, Excellent Oral Presentation Award, 7th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence (2023)
  2. Taketo Omi, Best Student Paper Award, 2023 International Symposium on Nonlinear Theory and Its Applications, Italy (2023)
  3. Hirozo Nakano, Student Paper Award, 2023 International Symposium on Nonlinear Theory and Its Applications, Italy (2023)
  4. 中野博三，竹水会優秀論文賞 (2024)
著書