Our faculty
Professor, Department of Mathematical Informatics,
Graduate School of Information Science and Technology,
the University of Tokyo
Room 253, 7-3-1 6 Hongo, Bunkyo-ku, Tokyo 113-8656
Tel: 03-5841-6920 ext. 26920 Fax:
E-mail: takeda@mist.i.u-tokyo.ac.jp
[ホームページ]
Biography
| March, 1996 | Bachelor of Engineering, Faculty of Science and Technology, Keio University |
|---|---|
| March, 1998 | M.A. in Administration Engineering, Graduate School of Science and Technology, Keio University |
| March, 2001 | Ph.D. in Mathematical and Computing Sciences, Tokyo Institute of Technology |
| April, 2001 | Researcher, Corporate R&D Center, Toshiba Corporation |
| April, 2003 | Assistant Professor, Department of Mathematical and Computing Sciences, Tokyo Institute of Technology |
| April, 2008 | Lecturer, Faculty of Science and Technology, Keio University |
| April, 2011 | Associate Professor, Faculty of Science and Technology, Keio University |
| April, 2013 | Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, the University of Tokyo |
| April, 2016 | Professor, Department of Mathematical Analysis and Statistical Inference, The Institute of Statistical Mathematics |
| April 2018 | Professor, Graduate School of Information Science and Technology, The University of Tokyo |
Research topics
We are conducting research focusing on formulating a mathematical optimization problem and developing an algorithm to solve the problem. In particular, we are developing efficient algorithms for continuous optimization problems, which are considered to be difficult to handle, such as optimization problems including uncertainty and non-convex optimization problems. Recently, I am interested in the topics below.
1: Efficient algorithms of continuous optimization problems focusing on non-convex optimization problems
2: Decision-making method for uncertain optimization problems: development of algorithms for robust optimization problems
3: Application of optimization methods to problems appearing in various fields (machine learning, financial engineering, energy system, etc.)
Major publications
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Jun-ya Gotoh, Akiko Takeda and Katsuya Tono, “DC formulations and algorithms for Sparse Optimization Problems”, mathematic Al Programming, First Online: 26 July 2017. (Solution study for sparse optimization problem)
Naoki Ito, Akiko Takeda and Kim-chuan Toh, “A Unified formulation and Fast Accelerated proximal Gradient for Classi Fication “, Journal of Machine Learning Research, 18, pp.1-49, 2017. (Application to machine learning)
Shinsaku Sakaue, Akiko Takeda, Sunyoung Kim and Naoki Ito, “Exact relaxations with truncated Moment for Binary Polynomial Optimization Problems “, SIAM Journal on Optimization, 27 (1), pp. 565-582, 2017. (SDP mitigation method for polynomial optimization problems)
Kosuke Nishida, Akiko Takeda, Satoru Iwata, Mariko Kiho and Isao Nakayama, “household, consumption prediction Ture selection of Lifestyle data “, IEEE International Conference on Smart Grid Communications, Dresden, Germany, 2017. (Application to energy systems)