Using the mathematics of probability to optimize machine learning and predictions.
Keywords: Probabilistic information processing, machine learning, data analysis, time series data, probabilistic simulation, annealing-type computer.
Artificial intelligence, machine learning, and simulation technologies are greatly changing our lives. On the other hand, there are issues such as environmental burdens from massive electricity consumption and the large-scale nature of training data. In order to significantly improve the efficiency of these information processing methods, I am conducting research that broadly explores various fields of mathematics, identifies usable technologies, and refines them into forms that can be applied in engineering. Although I am still in the research phase, I am able to accelerate predictions and controls by dozens of times using mathematics known as duality and Koopman operators, and I can compress neural networks used in artificial intelligence technologies. I am also aiming for machine learning with small amounts of data utilizing knowledge about the subject. Additionally, I am involved in research related to quantum computers known as annealing types, as well as simulations and estimations of probabilistic phenomena. Finding and refining usable mathematics can be challenging, but I aim to develop foundational technologies based on mathematics that are unique to universities.
- Company：埼玉大学 オープンイノベーションセンター
- Price：Other
