Refereed Journal Papers

  1. “Facial reduction and partial polyhedrality”, Bruno F. Lourenco, Masakazu Muramatsu, and Takashi Tsuchiya, SIAM Journal on Optimization, to appear, 2018.
  2. “An extension of Chubanov’s algorithm to symmetric cones”, Bruno F. Laurenco, Tomonari Kitahara, Masakazu Muramatsu and Takashi Tsuchiya, Mathematical Programming, to appear, 2018.
  3. Improved Simulation Adjusting, K. Hoki, N. Araki, S. Takahashi, and M. Muramatsu, ICGA journal, 39, 195-204, 2017.
  4. “Network Congestion Minimization Models Based on Robust Optimization”, Bimal Chandra Das, Satoshi Takahashi, Eiji Oki and Masakazu Muramatsu, IEICE TRANSACTIONS on Communications, 2017/ EBP, 3193-3193, 2017.
  5. “畳み込みニューラルネットワークを用いた囲碁における一局の棋譜からの棋力推定”, 荒木伸夫, 保木邦仁, 村松正和, 情報処理学会論文誌, 57巻, 11号, pp. 2365-2373, 2016.
  6. “Pure Nash Equilibria of Competitive Diffusion Process on Toroidal Grid Graphs”, Yuki Sukenari, Kunihito Hoki, Satoshi Takahashi and Masakazu Muramatsu, Discrete Applied Mathematics, Vol. 215, pp.31-40, 2016.
  7. “A Structural Geometrical Analysis of Weakly Infeasible SDPs”, Bruno F. Lourenço, Masakazu Muramatsu and Takashi Tsuchiya, Journal of Operations Research Society of Japan, Vol. 59, No. 3, pp. 241-257, 2016.
  8. “Weak infeasibility in second order cone programming”, Bruno F. Lourenço , Masakazu Muramatsu and Takashi Tsuchiya, Optimization letters, Vol. 10,pp. 1743-1755, 2015-12-24.
  9. “Perturbed sums-of-squares theorem for polynomial optimization and its applications”, Masakazu Muramatsua, Hayato Waki and Levent Tunçel, Optimization Methods and Software, Vol. 31, pp. 134-156, 2015/6/16.
  10. “Facial Reduction Algorithms for Conic Optimization Problems”, Hayato Waki and Masakazu Muramatsu, Journal of Optimization Theory and Applications, Vol. 158, pp. 188-215, 2013.
  11. “Efficiency of three forward-pruning techniques in shogi: futility pruning, null-move pruning, and late move reduction”, K. Hoki and M. Muramatsu, Entertainment Computing. Vol. 3, pp. 51-57, 2012.
  12. “Strange Behaviors of Interior-point Methods for Solving Semidefinite Programming Problems in Polynomial Optimization”, H.Waki, M.Nakata and M. Muramatsu, Computational Optimization and Applications, Vol. 53, pp. 823-844, DOI: 10.1007/s10589-011-9437-8-, 2011.
  13. “次の一手問題を用いた囲碁プレイヤの局面認識についての分析”, 高橋克吉, 村松正和, 伊藤毅志, 松原仁, 情報処理学会論文誌, 52巻, 12号, pp. 3796-3805, Dec-11.
  14. “An extension of the elimination method for a sparse SOS polynomial”, Hayato Waki and Masakazu Muramatsu, Journal of Operations Research Society of Japan, Vol. 54, No. 4, pp.161-190, 2011.
  15. “A facial reduction algorithm for finding sparse SOS representations”, Hayato Waki and Masakazu Muramatsu, Operations Research Letters, Vol. 38, pp. 361-365, 2010.
  16. “Implementation issues of second-order cone programming approaches for support vector machine learning problems”, Rameswar Debnath, Masakazu Muramatsu and Haruhiha Takahashi, IEICE Trans. Fundamentals.Vol. E92-A, pp. 1209-1222, 2009.
  17. “Invariance under affine transformation in semidefinite programming relaxation for polynomial optimization problems”, 脇隼人, 村松正和, 小島政和, Pacific Journal of Optimization, Vol. 5, pp. 297-312, 2009.
  18. “SparsePOP: a Sparse Semidefinite Programming Relaxation of Polynomial Optimization Problems”, Hayato Waki, Sunyoung Kim, Masakazu Kojima, Mazakazu Muramatsu and H. Sugimoto, ACM Transactions on Mathematical SoftwareVol. 35, Algorithm 883, 2008.
  19. “Equality based contraction of semidefinite programming relaxations in polynomial optimization”, Cong Vo, Masakazu Muramatsu and Masakazu Kojima, Journal of Operations Research Society of Japan, Vol. 51, No. 1, pp. 111-125, 2008.
  20. “囲碁における連数の最大値について”, 宮代隆平, 矢野洋平, 村松正和, 情報処理学会論文誌, 48巻, 11号, pp. 3463-3469, 2007.
  21. “An Extension of Sums of Squares Relaxations to Polynomial Optimization Problems over Symmetric Cones”, Masakazu Kojima and Masakazu Muramatsu, Mathematical Programming, Vol. 110, pp. 315-336, 2007.
  22. “Towards a pivoting procedure for a class of second-order cone programming problems having multiple cone constraints”, Masakazu Muramatsu, Pacific Journal of Optimization, Vol. 3, No. 1, pp. 87-98, 2007.
  23. “Sums of Squares and Semidefinite Programming Relaxations for Polynomial Optimization Problems with Structured Sparsity”, Hayato Waki, Sunyoung Kim, Masakazu Kojima and Masakazu Muramatsu, SIAM Journal on Optimization, Vol. 17, pp. 128-242, 2006.
  24. “2次錐計画のサブクラスに対する単体法的アルゴリズムにおけるピボット選択規則について”, 栗田圭介, 村松正和, 統計数理, 53巻, 1号, pp. 349-360, 2006.
  25. “A Pivoting Procedure for a Class of Second-Order Cone Programming”, Masakazu Muramatsu, Optimization Methods and Software, Vol. 21, pp. 295-315, 2006.
  26. “An efficient support vector machine learning method with second-order cone programming for large-scale problems”, Rameswar Debnath, Masakazu Muramatsu and Haruhisa Takahashi, Applied Intelligence, Vol. 23, pp. 219-239, 2005.
  27. “A Unified Class of Directly Solvable Semidefinite Programming Problems”, Masakazu Muramatsu, Annals of Operations Research, Vol. 133, pp. 85-97, 2005.
  28. “A New Second-Order Cone Programming Relaxation for MAX-CUT problems”, M.Muramatsu and T.Suzuki, Journal of Operations Research Society of Japan, Vol. 46, No. 2, pp. 164-177.
  29. “直列型生産ラインシステムにおける最適加工容量配分問題とその二次錐計画法による解法”, 石塚陽, 村松正和, 鷺森崇, 日本経営工学会論文誌, Vol. 52, No. 6, pp. 363-372, 2002.
  30. “On a commutative class of search directions for linear programming over symmetric cones”, Masakazu Muramatsu, Journal of Optimization Theory and Applications, Vol. 112, pp. 595-625, 2002.
  31. “The Gauss-Newton direction in semidefinite programming”, S. Kruk, F. Rendl, M. Muramatsu, R. J. Vanderbei and H. Wolkowicz, Optimization Methods and Software, Vol. 15, 2001.
  32. “On Network simplex method using the primal-dual symmetric pivoting rule”, M. Muramatsu, Journal of the Operations Research Socrety of Japan, Vol. 43, No. 1, pp. 149-161, 2000.
  33. “Commutative class and power class of search directions for symmetric cone linear programming”, M. Muramatsu, The first Sino-Japan Optimization Meeting (in Hong Kong), 2000.
  34. “On Commutative Class of Search Directions for Symmetric Cone Programming”, M. Muramatsu, International Symposium on Mathematical Programming (in Georgia Institute of Technology), 2000.
  35. “Primal-dual affine scaling algorithms fail for semidefinite programming”, M. Muramatsu and R. J. Vanderbei, Mathematics of Operations Research, Vol. 21, pp. 149-175, 1999.
  36. “Affine scaling algorithm fails for semidefinite programming”, Masakazu Muramatsu, Mathematical Programming, Vol. 83, pp. 393-406, 1998.
  37. “An affine scaling method with an infeasible starting point : analysis under nondegeneracy assumption”, Masakazu Muramatsu and Takashi Tsuchiya, Annals of Operations Research, Vol. 62, pp. 325-355, 1996.
  38. “Convergence analysis of the projective scaling aigorithm based on a long-step homogeneous affine scaling aigorithm”, Masakazu Muramatsu and Takashi Tsuchiya, Mathematical programming, Vol. 72, pp. 291-305, 1996.
  39. “Global convergence of a long-step affine scaling algorithm for degenerate linear programming problems”, Takashi Tsuchiya and Masakazu Muramatsu, SIAM Journal on Optimization, Vol. 5, pp. 525-551, 1995.

Conference Proceedings

  1. “Monte-Carlo Simulation Adjusting”, Nobuo Araki, Masakazu Muramatsu, Kunihito Hoki and Satoshi Takahashi, Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, pp. 3094-2095, 2014.
  2. “A New Model for Large Margin Classifiers by Second Order Cone Programming”, Rameswar Debnath, Masakazu Muramatsu and Haruhisa Takahashi, Proceedings of the International Conference on Artificial Intelligence 04 and Proceedings of the International Conference on Machine Learning; models, technologies, and applications 04, pp. 887-882, 2004.
  3. “The Support Vector Machine Learning Using the Second Order Cone Programming”, Rameswar Debnath, Masakazu Muramatsu and Haruhisa Takahashi, Proceedings of 2004 IEEE Interenational Joint Conference on Newral Networks and Fuzzy Logic, pp. 2991-2996, 2004.
  4. “Generalization of Kernel PCA and Automatic Parameter Tuning”, Takahide Nogayama, Masakazu Muramatsu and Haruhisa Takahashi, Proccedings of The ANZIIS 2003 Conference, pp. 173-178, 2003.

解説記事

  1. “ディープラーニングを用いたコンピュータ囲碁〜Alpha Goの技術と展望〜”, 伊藤毅志, 村松正和, 情報処理, 57巻, 4月号, pp.335-337, 2016.
  2. “面の話”, 村松正和, オペレーションズ・リサーチ, 57巻, 4月号, pp. 5-10, 2014.
  3. “ジョルダン代数”, 脇隼人, 村松正和, オペレーションズ・リサーチ, 55巻, 11月号, pp. 718-719, 2010.
  4. “二次錐計画”, 脇隼人, 村松正和, オペレーションズ・リサーチ, 55巻, 10月号, pp. 655-656, 2010.
  5. “コンピュータ囲碁の飛躍の背景”, 美添一樹, 村松正和, 数学セミナー, 49巻, 10月号, pp. 52-57, 2010.
  6. “プロ棋士対コンピュータ:FIT2008における囲碁対局報告”, 村松正和, 情報処理, 50巻, 1月号, pp. 70-73, 2009.
  7. “連続最適化における未解決問題”, 村松正和, オペレーションズ・リサーチ, 53巻, 1月号, pp. 10-14, 2008.
  8. “半正定値計画と内点法”, 村松正和, オペレーションズ・リサーチ, 52巻, 9月号, pp. 513-518, 2007.
  9. “多項式計画と錐線形計画 —非線形計画への線形計画からのアプローチ”, 村松正和, システム/制御/情報, 50巻, 9号, pp. 338-343, 2006.
  10. “錐線形計画への招待”, 村松正和, システム/制御/情報, 47巻, 5号, pp. 223-228, 2003.
  11. “アイスクリーム・コーンの中には何がある?”, 村松正和, システム/制御/情報, 44巻, 9号, pp. 541-542, 2000.

Other Papers

  1. “Infeasibility Detection in an Affine Scaling Infeasible Interior Doint Algorithm”, M. Muramatsu and T. Tsuchiya, Research Memorandum The Institute of Statistical Mathematics, No. 553, 1995.
  2. “An affine scaling method with an infeasible Starting Point”, M. Muramatsu and T. Tsuchiya, Research Memorandum (in The Institute of Statistical Mathematics), No. 490, 1993.
  3. “A Convergence analysis of a long-step variant of the projective scaling algorithm”, M. Muramatsu and T. Tsuchiya, Research Memorandum (in The Institute of Statistical Mathematics), No. 454, 1993.