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Lab. 3 Ken’ichiro Tanaka

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Ken’ichiro Tanaka（田中　健一郎）
田中　健一郎

Department of Mathematical Informatics,
Graduate School of Information Science and Technology,
University of Tokyo
Associate Professor

7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656
Eng. 6 Bldg. Room 342
Tel: +81-3-5841-6439, ext. 26439
Fax:

E-mail：kenichiro＠mist.i.u-tokyo.ac.jp

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Curriculum Vitae

Mar. 2002 Graduated from the Department of Mathematical Engineering and Information Physics, School of Engineering, The University of Tokyo
Mar. 2004 Graduated from the Master Course of the Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo
Mar. 2007 Graduated from the Doctor Course of the Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo
Apr. 2007 – Mar. 2011 Tokio Marine & Nichido Fire Insurance Co., Ltd.
Apr. 2011 – Mar. 2015 Assistant Professor, School of Systems Information Science, Department of Complex and Intelligent Systems, Future University Hakodate
Apr. 2015 – Mar. 2017 Associate Professor, Department of Mathematical Engineering, Faculty of Engineering, Musashino University
Apr. 2017 – Associate Professor, Department of Mathematical Informatics, Graduate School of Information Science and Technology, University of Tokyo

Research Themes

Numerical analysis，in particular, theory and application related to function approximation and numerical integration.

Function approximation and numerical integration are bases of various computational methods for problems in mathematical analysis such as differential equations. I have been engaged mainly in design and analysis of accurate approximation formulas for analytic functions by means of complex analytic methods. In particular, I’m interested in analysis and application of formulas (such as the DE formulas and DE-Sinc formulas) derived by the double-exponential (DE) transformations proposed by Takahasi and Mori. Recently, I’m developing general frameworks for designing accurate approximation formulas.

Selected Publications

Ken’ichiro Tanaka, Tomoaki Okayama, and Masaaki Sugihara, Potential theoretic approach to design of accurate formulas for function approximation in symmetric weighted Hardy spaces, IMA Journal of Numerical Analysis, Volume 37, Issue 2 (2017), pp. 861-904 (doi:10.1093/imanum/drw022).

Ken’ichiro Tanaka, A fast and accurate numerical method for the symmetric Levy processes based on the Fourier transform and sinc-Gauss sampling formula, IMA Journal of Numerical Analysis, Volume 36, Issue 3 (2016), pp. 1362-1388 (doi:10.1093/imanum/drv038).

Ken’ichiro Tanaka and Alexis Akira Toda, Discretizing distributions with exact moments: error estimate and convergence analysis, SIAM Journal on Numerical Analysis, Volume 53, Issue 5 (2015), pp. 2158-2177 (doi:10.1137/140971269).

Sunao Murashige and Ken’ichiro Tanaka, A new method of convergence acceleration of series expansion for analytic functions in the complex domain, Japan Journal of Industrial and Applied Mathematics, Volume 32, Issue 1 (2015), pp. 95-117 (doi: 10.1007/s13160-014-0159-z).

Tomoaki Okayama, Ken’ichiro Tanaka, Takayasu Matsuo, and Masaaki Sugihara, DE-Sinc methods have almost the same convergence property as SE-Sinc methods even for a family of functions fitting the SE-Sinc methods Part I: Definite integration and function approximation, Numerische Mathematik, Volume 125, Issue 3 (2013), pp. 511-543 (doi: 10.1007/s00211-013-0540-x).

Ken’ichiro Tanaka, Masaaki Sugihara, Kazuo Murota, and Masatake Mori, Function classes for double exponential integration formulas, Numerische Mathematik, Volume 111, Issue 4 (2009), pp. 631-655 (doi: 10.1007/s00211-008-0195-1).

Akiko Takeda

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Akiko Takeda
Akiko Takeda

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

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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

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)