Research theme for competitive and other funds (5)：
2024 - 2027 Theory of Optimal Latent Space with Its Applications to Economics, Medicine and Generative AI
2019 - 2024 予兆検知のための数理的手法の開発と経済学・医学への応用
2019 - 2022 Discovery of Deep Knowledge with Advanced Utilization of Latent Space
2013 - 2019 Discovery of Deep Knowledge and Value Creation from Complex Data
2011 - 2016 Study on Information theoretic Learning Theory of Latent Dynamics
Papers (126)：
N. Nishikawa, Y. Ike, K. Yamanishi. Adaptive Topological Features via Persistent Homology Filetering Learning for Point Clouds. NeurIPS2023. 2023
Shintaro Fukushima, Kenji Yamanishi. Balancing Summarization and Change Detection in Graph Streams. ICDM. 2023. abs/2311.18694
R.Yuki, A.Suzuki, K. Yamanishi. Dimensionality and Curvature Selection of Graph Embedding using DNML Code-Length. ICDM. 2023. 1517-1522
Kenji Yamanishi, So Hirai. Detecting signs of model change with continuous model selection based on descriptive dimensionality. Applied Intelligence. 2023
Ryo Yuki, Yuichi Ike, Kenji Yamanishi. Dimensionality selection for hyperbolic embeddings using decomposed normalized maximum likelihood code-length. Knowledge and Information Systems. 2023. 65. 12. 5601-5634
2009 - 現在 The University of Tokyo The Graduate School of Information Science and Technology Professor
1987/04 - 2008/12 NEC
Awards (5)：
2024/05 - Institute of Electoronics, Information and Communication Engineers Fellow Creation of Information-theoretic Learning Theory and Its Applications to Data Science
2015/04 - Faculty of Engineering, the University of Tokyo Best Teaching Award Probability Mathmatical Engineering
2014/06 - IBM IBM Faculty Award Information-theoretic learning theory and anomaly detection
2005/07 - Fujisankei Business Eye Advanced Technology, Fujisankei Business Eye Award Research and Development of Security Intelligence Based on Data Mining
1991/04 - Institute of Electoronics, Information and Communication Engineers Best paper award On Asymptotic Performance of Binary Modular Codes
