論文

• Tianxiang Liu, Ivan Markovsky, Ting Kei Pong, Akiko Takeda. A hybrid penalty method for a class of optimization problems with multiple rank constraints, SIAM Journal on Matrix Analysis and Applications, Sept. 2020.  公式リンク  
  
• Ivan Markovsky, Tianxiang Liu, Akiko Takeda. Data-Driven Structured Noise Filtering via Common Dynamics Estimation, IEEE Transactions on Signal Processing, May 2020.  公式リンク  
  
• Tianxiang Liu, Ting Kei Pong, Akiko Takeda. A refined convergence analysis of pDCAe with applications to simultaneous sparse recovery and outlier detection, Computational Optimization and Applications, Jan. 2019.  公式リンク  
  
• Tianxiang Liu, Ting Kei Pong, Akiko Takeda. A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems, Mathematical Programming, Sept. 2018.  公式リンク  
  
• Takafumi Kanamori, Shuhei Fujiwara, Akiko Takeda. Robustness of Learning Algorithms using Hinge Loss with Outlier Indicators, Neural Networks, Vol. 94, pp. 173--191, Oct. 2017.
• Shuhei Fujiwara, Akiko Takeda, Takafumi Kanamori. DC Algorithm for Extended Robust Support Vector Machine, Neural Computation, vol. 29, num. 5, pp. 1406--1438, May 2017.
• Tomohiko Mizutani, Akiko Takeda. DEMiCs: A software package for computing the mixed volume via dynamic enumeration of all mixed cell, Software for Algebraic Geometry, IMA Volumes in Mathematics and its Applications, Springer, Vol. 148, pp. 59-79, 2008.  公式リンク  
  
• 水谷友彦, 武田朗子, 小島政和. Dynamic Enumeration of All Mixed Cells, Discrete and Computational Geometry, Vol. 37, No. 3, pp. 351-367, May 2007.
• J. Gotoh, A. Takeda. A Linear Classification Model Based on Conditinal Geometric Score, Pacific Journal of Optimization, Vol. 1, pp. 277-296, 2005.
• 武田朗子, 内平直志, 中本政志, 松本茂. 不確実な電力事業環境下における設備投資計画手法, 日本経営工学会論文誌, Vol. 56, pp. 366-376, 2005.
• T. Gunji, S. Kim, M. Kojima, A. Takeda, K. Fujisawa, T. Mizutani. PHoM -- a Polyhedral Homotopy Continuation Method, Computing, Vol. 73, pp. 57-77, 2004.
• C. Vo, A. Takeda, M. Kojima. A Multilevel Parallelized Hybrid Branch and Bound Algorithm for Quadratic Optimization, IPSJ Transactions on Advanced Computing Systems, Vol. 45, No. SIG 6(ACS 6), pp. 186-196, 2004.
• K. Fujisawa, M. Kojima, A. Takeda, M. Yamashita. Solving Large Scale Optimization Problems via Grid and Cluster Computing, Journal of the Operations Research Society of Japan, Vol. 47, pp. 265-274, 2004.
• A.Takeda, K.Fujisawa, Y.Fukaya, M.Kojima. Parallel Implementation of Successive Convex Relaxation Methods for Quadratic Optimization Problems, Journal of Global Optimization, 24, pp. 237-260, 2002.
• Akiko Takeda. Complexity Analysis of Conceptual Successive Convex Relaxation of Nonconvex Sets, Mathematics of Operations Research, Vol. 26, pp. 519-542, 2001.
• A.Takeda, H.Nishino. On Measuring the Inefficiency with the Inner-Product Norm in Date Envelopment Analysis, European Journal of Operational Research, Vol. 133, No. 2, pp. 377-393, 2001.
• Akiko Takeda. Successive Convex Relaxation Approach to Bilevel Quadratic Optimization Problems, M. C. Ferris, O. L. Mangasarian and J.S. Pang (Eds.), Applications and Algorithms of Complementarity, 2001.
• Akiko Takeda. Towards the Implementation of Successive Convex Relaxation Method for Nonconvex Quadratic Optimization Problems, P.M. Pardalos (Ed.), Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems, 2000.

国際会議発表 (査読有り)

• Katsuki Fujisawa, Masakazu Kojima, Akiko Takeda, Makoto Yamashita. High Performance Grid and Cluster Computing for Some Optimization Problems, Proceedings of SAINT 2004 Work Shops, 2004.
• Akiko Takeda, Yang Dai, Mituhiro Fukuda, Masakazu Kojima. Towards implementations of successive convex relaxation methods for nonconvex quadratic optimization problems, Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems, Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems (P. M. Pardalos, Ed.), Kluwer Academic Publishers (Dorchecht), pp. 489-510, 2000.

国際会議発表 (査読なし・不明)

• Tianxiang Liu, Ting Kei Pong, Akiko Takeda. A successive difference-of-convex approximation method with applications to control problems, ICCOPT 2019, Aug. 2019.
• Tianxiang Liu, Ivan Markovsky, Ting Kei Pong, Akiko Takeda. A hybrid penalty method for a class of optimization problems with multiple rank constraints, NACA-ICOTA2019, Aug. 2019.
• Tianxiang Liu, Ting Kei Pong, Akiko Takeda. A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems, 29th European Conference on Operational Research, July 2018.
• Tianxiang Liu, Ting Kei Pong, Akiko Takeda. A successive difference-of-convex approximation method for a class of nonconvex nonsmooth optimization problems, 23rd International Symposium on Mathematical Programming, July 2018.

国内会議発表 (査読なし・不明)

• Tianxiang Liu, Akiko Takeda. An inexact successive quadratic approximation method for a class of difference-of-convex optimization problems, 研究集会最適化：モデリングとアルゴリズム, Mar. 2021.
• 藤沢 克樹, 武田 朗子, 小島 政和, 中田 和秀. 広域分散コンピューティング環境における数理計画ソフトウェアSDPA, 情報処理学会研究報告. HPC, 情報処理学会研究報告. HPC, Vol. 83, pp. 31-36, May 2001.
• 藤沢 克樹, 武田 朗子, 小島 政和, 中田 和秀. 半正定値計画問題に対するソフトウェアSDPAの広域並列計算システム, 研究集会「最適化の数理科学」, 数理解析研究所講究録, Vol. 1174, pp. 138-145, 2000.
• 藤沢 克樹, 武田 朗子, 小島 政和, 中田 和秀. 半正定値計画問題に対するソフトウェアSDPAの広域並列計算システム, 統計数理研究所研究集会 最適化：モデリングとアルゴリズム１４, 統計数理研究所共同研究レポート, Vol. 135, 215-222, 2000.

その他の論文・著書など

• 中田 和秀, 下平 英寿, 武田 朗子, 小林 和博. 第１５回RAMPシンポジウムルポ, オペレーションズ・リサーチ, Vol. 49, pp. 256-257, 2004.

学位論文

• Successive Convex Relaxation Methods for Nonconvex Quadratic Optimization Problems,  本文,  Doctor of Science,  Tokyo Institute of Technology,  2001/--/--, 
• 効率評価の困難な投入・産出活動の効率性分類とその安定性分析,  Master of Engineering,  Keio University,  1998/--/--, 

[ BibTeX 形式で保存 ]    [ 論文・著書をCSV形式で保存 ]    [ 特許をCSV形式で保存 ]