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教授紹介

早稲田大学理工学術院教授 松山泰男

早稲田大学名誉教授
同 理工学研究所名誉研究員
Founder of the α-EM algorithm

松山泰男
Yasuo Matsuyama

yasuo2-at-waseda.jp
http://www.f.waseda.jp/yasuo2/

記号とパターンを統合するhuman-awareなIoCT:
松山教授は,機械学習と計算知能に基づいて インテリジェントなhuman-aware IoCTを実現するための研究を行っている. IoCTは,Internet of Collaborative Thingsを意味する. また,同教授はα-EMアルゴリズムの創始者として知られている.

  • 機械学習とブロックチェーンの連動
  • 大量多様なデータの処理とブロックチェーン(IoCT)
  • 一般化された情報量による学習アルゴリズム
  • 動画像,静止画像の検索エンジン
  • ブレインマシンインターフェース
  • ニューラルネットワーク
  • バイオインフォマティクス

経 歴

2017年-現在

早稲田大学名誉教授,理工学研究所名誉研究員

1996-2017年

早稲田大学理工学術院教授(情報理工学科)

  この間, メディアネットワークセンター所長(2011-2014)

1994年

人事院試験専門委員(併任:国家 I 種総合試験)

1979-96年

茨城大学講師,助教授,教授(1995-96:博士課程専攻長)

1978年

スタンフォード大学大学院 工学研究科 電気工学専攻 博士課程修了(Ph.D.)

1977-78年

スタンフォード大学情報システム研究所助手

1974-78年

日米人物交換フェロー(日本学術振興会,フルブライト,IIE)

1974年

早稲田大学大学院 理工学研究科 電気工学専攻 博士課程修了(工学博士)

1971年

早稲田大学大学院 理工学研究科 電気工学専攻 修士課程修了修了(工学修士)

1969年

早稲田大学理工学部 電気工学科卒業 (工学士)

所属学会

国外

IEEE,ACM

国内

電子情報通信学会,情報処理学会,日本神経回路学会

受 賞

14

大隈記念学術褒賞記念賞 (2016)

13

WASEDA e-Teaching Award (2016)

12

情報処理学会優秀教材賞(教科書)(2015)

11

情報処理学会フェロー (2014)

10

IEEE Life Fellow (2013)

9

CSTST (International Conference on Soft Compating as Transdisciplinary Science and Technology)

Best Paper Award, ACM & IEEE (2008)
8

LSI IPデザイン・アワード 知的財産賞 (2006)

7

APNNA Best Paper Award for Application Oriented Research (2004)

6

電子情報通信学会フェロー (2002)

5

IEEE Transactions on Neural Networks, Outst3446-anding Paper Award (2001)

4

電気通信普及財団賞テレコムシステム技術賞本賞 (2001)

3

IEEE Fellow(1998)

2

電子情報通信学会論文賞(1992)

1

電気通信普及財団賞テレコムシステム技術賞奨励賞 (1989)

主要発表物

* Y. Matsuyama, Divergence family contribution to data evaluation in blockchain via alpha-EM and log-EM algorithms, IEEE Access, Vol. 9, pp. 24546-24559, 2020. DOI: 10.1109/ACCESS.2012.3056710
  Y. Matsuyama, Divergence family attains blockchain applications via α-EM algorithm, Proceedings of IEEE International Symposium on Information Theory, pp. 727-731, 2019. DOI: 10.1109/ISIT.2019.8849300
* T. Horie, M. Uchida, Y. Matsuyama, Similar video retrieval via order-aware exemplars and alignment, Journal of Signal and Information Processing, vol.9, pp. 73-91, 2018. DOI: 10.4236/jsip.2018.92005
 * Y. Matsuyama, The alpha-HMM estimation algorithm: Prior cycle guides fast paths, IEEE Trans. Signal Processing, Vol. 65, pp. 3446-3461, and 6-page supplementary materials, 2017. DOI: 10.1109/TSP.2017.2692724
* Y. Matsuyama, Human-aware IoCT via machine learning and HPC, Invited talk at the 15th HPC Connection Workshop, Wuxi, April, 2017. http://www.asc-events.org/ASC17/Workshop.php
* H. Iwase, T. Horie, and Y. Matsuyama, (corresponding author), Verification of fraudulent PIN holders by brain waves, Proc. Int. Joint Conf. Neural Networks, pp. 2068-2075, Vancouver, 2016.
* T. Horie, M. Moriwaki, R. Yokote, S. Ninomiya, A. Shikano, Y. Matsuyama, Similar-video retrieval via learned exemplars and time-warped alignment, Lecture Notes in Computer Science, No. 8836, pp. 85-94. DOI: 10.1007/978-3-319-12643-2_11. http://link.springer.com/chapter/10.1007%2F978-3-319-12643-2_11
* Y. Matsuyama, Machine Learning Strategies for Big Data Utilization: Assembling via Statistical Soft Label, Plenary/Keynote Speak, Int. Conf. Audio, Language and Image Processing, Shanghai, July, (2014) http://www.icalip2014.org/KeynoteSpeakerMatsuyama.aspx   presentation
* H. Kamiya, R. Yokote and Y. Matsuyama, Icon Placement Regularization for Jammed Profiles: Applications to Web-Registered Personnel Mining, Communications in Computer and Information Science, Vol. 409, pp. 70-79, 2013. http://link.springer.com/book/10.1007%2F978-3-319-03783-7
* M. Shozawa, R. Yokote, S. Hidano, Chi-Hua Wu and Y. Matsuyama, Brain Signal Based Continuous Authentication: Functional NIRS Approach, Lecture Notes in Computer Science, Vol. 7903, pp. 171-180, 2013. http://link.springer.com/book/10.1007%2F978-3-642-38679-4
* M. Maejima, R. Yokote, Y. Matsuyama, Composite data mapping by multi-dimensional scaling: GUI design for clustering must-watch and no-need programs, Lecture Notes in Computer Science, No. 7667, pp. 267-274, 2012.
* R. Yokote and Y. Matsuyama, Rapid algorithm for independent component analysis, J. Signal and Information Processing, Vol. 3, pp. 275-285, 2012.
* Y. Matsuyama, R. Yokote, Y. Yokosawa, Conversion of sensitivity-based tasks from brain signals and motions: Applications to humanoid operation, Proc. IASTED Int. Conf. on Artificial Intelligence, pp. 271-277, 2012.
* Y. Matsuyama and R. Yokote, From convex divergence to human-aware information processing: Good models mismatch well, therefore serviceable, International Workshop on Anomalous Statistics, Generalized Entropies, and Information Geometry, invited presentation, Abstract p. 20, Nara, Japan, March 2012.
* Y. Matsuyama, Hidden Markov model estimation based on the alpha-EM algorithm: Discrete and continuous alpha-HMMs, Proc. of International Joint Conference on Neural Networks, pp. 809-816, San Jose, CA, 2011.
* R. Yokote, T. Nakamura and Y. Matsuyama, Independent component analysis with graphical correlation: Applications to multi-vision coding, Proceedings of International Joint Conference on Neural Networks, San Jose, CA, pp. 701-708, 2011.
* Y. Matsuyama, R. Hayashi and R. Yokote, Fast estimation of hidden Markov models via alpha-EM algorithm, Proc. of 2011 IEEE Statistical Signal Processing Workshop, Nice, France, pp. 89-92, 2011.
* 松山泰男、 バイオインフォマティクス in silico, 培風館, 2011.
* Y. Matsuyama, K. Noguchi, T. Hatakeyama, N. Ochiai and T. Hori, Signal recognition and conversion towards symbiosis with ambulatory humanoids, Lecture Notes in Artificial Intelligence, Springer, No.6334, pp. 101-111, 2010.
* Y. Matsuyama and R. Hayashi, Alpha-EM gives fast hidden Markov model estimation: Derivation and evaluation of alpha-HMM, Proc. Int. Joint Conf. on Neural Networks, pp. 663-670, 2010.
* R. Yokote and Y. Matsuyama, Yet rapid ICA: Applications to un-indexed image-to-image retrieval, Proc. Int. Joint Conf. on Neural Networks, pp. 4255-4262, 2010.
Bio-signal integration for humanoid operation: Gesture and brain signal recognition by HMM/SVM-embedded BN, Lecture Notes in Computer Science, No. 5506, pp. 351-359, 2009.
* T. Kato, S. Honma, Y. Matsuyama, T. Yoshino and Y. Hoshino, Sensibility-aware image retrieval using computationally learned bases: RIM, JPG, J2K and their mixtures, Lecture Notes in Computer Science, No. 5506, pp. 620-627, 2009.
* M. Takata and Y. Matsuyama, Protein folding classification by committee SVM array, Lecture Notes in Computer Science, No. 5507, pp. 369-377, 2009.
* Y. Matsuyama, F. Matsushima, Y. Nishida, T. Hatakeyama, N. Ochiai and S. Aida, Multimodal belief integration by HMM/SVM-embedded Bayesian network: Applications to ambulating PC operation by body motions and brain signals, Lecture Notes in Computer Science, No. 5768, pp. 767-778, 2009.
* Y. Matsuyama and Y. Nishida, HMM-embedded Bayesian network for heterogeneous command integration: Applications to biped humanoid operation over the network, Proc. CSTST 2008, pp.138-145, 2008.
* Y. Matsuyama, F. Ohashi, F. Horiike, T. Nakamura, S. Honma, N. Katsumata, and Y. Hoshino, Image-to-image retrieval using computationally learned bases and color information, Proc. IJCNN, 1158, 2007.
* Y. Matsuyama, Y. Ishihara, Y. Ito, T. Hotta, K. Kawasaki, T. Hasegawa and M. Takata, Promoter recognition involving motif detection : Studies on E. coli and human genes, ISMB/ECCB, H06, 2007.
* J. Kato, N. Takahashi, Y. Ueda, Y. Sugihara and Y. Matsuyama, Networked remote operation of humanoid via motion interpretation and image recognition, Proceedings of Int. Conf. on Autonomous Robots and Agents, Vol. 1, pp. 51-56, 2006.
* N. Katsumata, Y. Matsuyama, T. Chikagawa, F. Ohashi, F. Horiike, S. Honma and T. Nakamura, Retrieval-aware image compression, its format and viewer based upon learned bases, Lecture Notes in Computer Science, No. 4233, pp. 420-429, 2006.
* Y. Matsuyama, K. Onuki, Y. Ito, Y. Ishihara, k. Kawasaki and T. Hasegawa, Decomposition of DNA sequences into hidden components; Applications to human genome's promoter recognition, Intelligent Systems for Molecular Biology, H67, 2006.
* 河北、寶崎、松山、 Fake Processインターリーバを用いたターボ符号器とその復号器, 第8回LSI IPデザイン・アワード論文,2006.
* Y. Matsuyama, T. Shiga, T. Chikagawa, N. Takahashi and Y. Ueda, Network communication strategies for cooperative physical agents, Proceedings of Asia-Pacific Symposium on Information and Telecommunication Technologies, Vol. 1, pp. 148-153, 2005.
* Y. Matsuyama, Y. Ito, K. Onuki and Y. Ishihara, Decomposition of Discrete-symbol biosequences to hidden components: Independent component analysis for DNA promoter recognition, Proceedings of International Conference on Neural Information Processing, Vol. 1, pp. 538-543, 2005.
* N. Katsumata and Y. Matsuyama, Database retrieval for similar images using ICA and PCA bases, Engineering Applications of Artificial Intelligence, Vol. 18, pp. 705-717, 2005.
* Y. Matsuyama, S. Yoshinaga, H. Okuda, K. Fukumoto, S. Nagatsuma, K. Tanikawa, H. Hakui, R. Okuhara and N. Katsumata, Towards the unification of human movement, animation and humanoid in the network, Lecture Notes in Computer Science, Springer Verlag, No. 3316, pp. 1135-1141, 2004.(APPNA Best Paper Award for Application Oriented Research)
* Y. Matsuyama and R. Kawamura, Promoter recognition for E. coli DNA segments by independent component analysis, Proc. Computational Systems Bioinformatics, Vol. 1, pp. 686-691, 2004.
* Y. Matsuyama, H. Kataoka, N. Katsumata and K. Shimoda, ICA photographic encoding gear: Image bases towards IPEG, Proc. IJCNN, vol. 3, pp. 2129-2134, 2004.
* N. Nishioka, Y. Matsuyama, A. Saitoh, Y. Morita, N. Katsumata, H. Kataoka, R. Mizuta and S. Yoshika, Agent generation and resource allocation in a network computing environment, Proc. Asia-Pacific Symposium on Information and Telecommunication Technologies, Proc. Asia-Paific Symposium on Information and Telecommunication Technologies, Vol. 1, pp. 63-68, 2003.
* Y. Matsuyama, N. Katsumata and R. Kawamura, Independent component analysis minimizing convex divergence, Lecture Notes in Computer Science, Springer Verlag, No. 2714, pp. 27-34, 2003.
* Y. Matsuyama, The alpha-EM algorithm: Surrogate likelihood maximization using alpha-logarithmic information measures, IEEE Trans. on Information Theory, Vol. 49, pp. 692-706, 2003.
* Y. Matsuyama, S. Imahara and N. Katsumata, Optimization transfer for computational learning: A hierarchy from f-ICA and alpha-EM to their offsprings, Proceedings of International Joint Conference on Neural Networks, Vol. 3, pp. 1883-1888, 2002.
* Y. Matsuyama, N. Katsumata, Y. Suzuki and S. Imahara, The alpha-ICA algorithm, Proceedings of Independent Component Analysis and Blind Signal Separation, pp. 297-302, 2000.
* 松山泰男、 α-EMアルゴリズムとその基本的性質, 電子情報通信学会論文誌D-I, Vol. J82-D-I,pp. 1347-1358, 1999. (電気通信普及財団賞テレコムシステム技術賞本賞,2001; 電子情報通信学会フェロー対象論文,2002)
* Y. Matsuyama, Multiple descent cost competition: Restorable self-organization and multimedia information processing, IEEE Trans. on Neural Networks,Vol. 7,pp. 652-668, 1998. (Outstanding Paper Award of IEEE Trans. NN, 2001; 電子情報通信学会フェロー対象論文, 2002)
* 松山泰男、 自己組織化と外部知性との結合 架空のコンピュータHALの生誕年によせて, 情報処理,Vol. 39,pp. 37-42, 1998.
* 岡本、松山、大島、 コンピュータ理工学辞典,共立出版社,1997.
* Y. Matsuyama, The alpha-EM Algorithm: A block connectable generalized learning tool for neural networks, Lecture Notes in Computer Science, Springer Verlag, No. 1240, pp. 1240,483-492, 1997. (IEEE Fellow Award対象論文,1998)
* Y. Matsuyama, Harmonic competition: A self-organizing multiple criteria optimization, IEEE Trans. on Neural Networks,Vol. 7,pp. 652-668, 1996. (IEEE Fellow Award対象論文,1998)
* 藤井、松山、 動的計画法を用いたステレオマッチングにおける順序逆転問題の 一解法, 電子情報通信学会論文誌,Vol. J79-D-II, pp. 775-784, 1996.
* Y. Matsuyama, Competitive learning among massively parallel agents: Applications to traveling salesperson problems, Neural, Parallel & Scientific Computations, Vol. 1, pp. 181-197, 1993.
* 松山泰男、 自己組織化できるニューラルネットワークと ユークリッド空間におけるいろいろな巡回セールスマン問題, 電子情報通信学会論文誌,Vol. J74-D-II, pp. 416-425, 1991. (電子情報通信学会論文賞,1992; International Abstracts of Operations Research誌推薦採録, 1992; 電子情報通信学会フェロー対象論文,2002)
* 松山泰男、 多重降下競合アルゴリズムと並列部分最適化,情報処理学会論文誌,Vol. 32, pp. 333-344, 1991.
* Y. Matsuyama, Vector quantization of optimally grouped sets and image/speech compression, Proceedings of IEEE International Conference on Global Communications (GLOBECOM), Vol. 3, pp. 957-961, 1987. (電気通信普及財団賞テレコムシステム技術賞奨励賞, 1989)
* 松山、富沢、 VLSI設計入門,共立出版社,1983.
* Y. Matsuyama and R. M. Gray, Voice coding and tree encoding speech compression systems based upon inverse filter matching, IEEE Trans. on Communications, Vol. COM-30, pp. 711-720, 1982. (IEEE Fellow Award対象論文,1998)
* 松山泰男、 逆フィルタ符号帳を用いた2種類の音声圧縮システム, 電子通信学会論文誌,Vol. J64-A, pp. 659-666, 1981. (電子情報通信学会フェロー対象論文,2002)
* Y. Matsuyama and R. M. Gray, Universal tree encoding for speech, IEEE Trans. Information Theory, Vol. IT-27, pp. 31-40, 1981. (IEEE Fellow Award対象論文,1998)
* R. M. Gray, A. Buzo, A. H. Gray, Jr. and Y. Matsuyama, Distortion measures for speech processing, IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. ASSP-24, pp. 367-376, 1980 (IEEE Fellow Award対象論文,1998).
* Y. Matsuyama, Mismatch robustness of linear prediction and its relationship to coding, Information and Control (Information and Computation), Vol. 47. pp. 237-262, 1980. (IEEE Fellow Award対象論文,1998)
* 松山泰男、 ユニバーサルな情報源符号化と音声圧縮, 電子通信学会論文誌,Vol. 62-A, pp. 887-894, 1979. (電子情報通信学会フェロー対象論文,2002)
* Y. Matsuyama, Process distortion measures and signal processing, Ph.D. Dissertation, Stanford University, Aug., 1978.
* Y. Matsuyama, A note on stochastic modeling of shunting inhibition, Biological Cybernetics, Vol. 24, pp. 139-145, 1976.
* Y. Matsuyama, K. Shirai and K. Akizuki, On some properties of stochastic information processes in neurons and neuron populations, Kybernetik (Biological Cybernetics), Vol. 15, pp. 127-145, 1974.
* Y. Matsuyama, Studies on stochastic modeling of neurons, Dr. Engineering Dissertation, Waseda University, Mar., 1974.

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