研究室紹介

Machine Learning Theory

Department of Informatics, Faculty of Information Science and Electrical Engineering

Department of Informatics, Graduate School of Information Science and Electrical Engineering

Department of Electrical Engineering and Computer Science, School of Engineering

The problem of decision-making by predicting future data from the past arise in many applications such as stock investment, item recommendation, routing, updating kana-kanji conversion dictionary, and so on. Our group is trying to develop ingenious methods of decision-making for various problems by using machine learning techniques. On the other hand, we also apply the methods developed to optimization problems in machine learning. Furthermore, for various classes for knowledge representation such as Boolean circuits, decision diagrams, neural networks, comparator networks, we investigate their mathematical properties and relationships between them, thereby we analyze computational efficiency of decision making methods. The problem of decision-making by predicting future data from the past arise in many applications such as stock investment, item recommendation, routing, updating kana-kanji conversion dictionary, and so on. Our group is trying to develop ingenious methods of decision-making for various problems by using machine learning techniques. On the other hand, we also apply the methods developed to optimization problems in machine learning. Furthermore, for various classes for knowledge representation such as Boolean circuits, decision diagrams, neural networks, comparator networks, we investigate their mathematical properties and relationships between them, thereby we analyze computational efficiency of decision making methods.

Staff

Prof. Eiji Takimoto
Assoc.Prof. Kohei Hatano

The Main Research Topics

  • Online decision making
  • Computational learning theory
  • Computational compelxity
« back