- JST Home
- /
- Strategic Basic Research Programs
- /
- PRESTO
- /
- project/
- Collaborative Mathematics for Real World Issues/
- [Kenji Nagata] Development of data-driven science based on computational algebraic geometry
National Institute of Advanced Industrial Science and Technology (AIST)
Senior Researcher
For the statistical stochastic models with hierarchical structure such as Deep networks, Gaussian mixture models and hidden Markov models, algebraic geometry have contributed to the performance elucidation of statistical learning. Based on this knowledge, this study develops a new technology of data-driven approach with Bayesian estimation. Moreover, this study promotes an academic area to be called computational algebraic geometry with the knowledge of computer science and statistics.