Frontier Computational Intelligence Laboratory yasuo2@waseda.jp Around 30 members in this laboratory. 
Novel information processing paradigm unifying symbols and patterns:

1996 
Waseda University, Full Professor (Department of Computer Science and Engineering)（2011 ）Director of the Media Network Center 
1994 
National Personnel Authority, CoChief Examiner (Dual position): Comprehensive Examination of Grade 1 
197996 
Ibaraki University, {Assistant > Associate > Full} Professor} 
1978 
Stanford University, Graduate School, EE Major: Ph.D. 
197778 
Stanford University Information Systems Laboratory, Research Assistant 
197478 
JapanUS Exchange Fellow (Japan Society for the Promotion of Science) 
1974 
Waseda University, Graduate School, EE Major: Dr. Engineering 
1969 
Waseda University, Department of Electrical Engineering: B. Engineering 
International 
IEEE, ACM, ISMB 
National 
IEICE (The Institute of Electrical, Communications and Information Engineers), 
9 
CSTST (International Conference on Soft Computing as Transdisciplinary Science and Technology) Best Paper Award, ACM & IEEE (2008) 
8 
LSI IP Design Award, Intellectual Product Award (2006) 
7 
APNNA Best Paper Award for Application Oriented Research (2004) 
6 
Fellow Award of IEICE (2002) 
5 
IEEE Transactions on Neural Networks, Outstanding Paper Award (2001) 
4 
The Telecommunications Advancement Foundation, Telecommunication Systems Technology, Major Award (2001) 
3 
IEEE Fellow Award (1998) 
2 
IEICE Transactions, Best Paper Award (1992) 
1 
The Telecommunications Advancement Foundation, Telecommunication Systems Technology, Promotion Award (1989) 
* H. Kamiya, R. Yokote and Y. Matsuyama, Icon Placement Regularization for Jammed Profiles: Applications to WebRegistered Personnel Mining, Communications in Computer and Information Science, Vol. 409, pp. 7079, 2013. http://link.springer.com/book/10.1007%2F9783319037837 
* M. Shozawa, R. Yokote, S. Hidano, ChiHua Wu and Y. Matsuyama, Brain Signal Based Continuous Authentication: Functional NIRS Approach, Lecture Notes in Computer Science, Vol. 7903, pp. 171180, 2013. http://link.springer.com/book/10.1007%2F9783642386794 
* M. Maejima, R. Yokote, Y. Matsuyama, Composite data mapping by multidimensional scaling: GUI design for clustering mustwatch and noneed programs, Lecture Notes in Computer Science, No. 7667, pp. 267274, 2012. 
* R. Yokote and Y. Matsuyama, Rapid algorithm for independent component analysis, J. Signal and Information Processing, Vol. 3, pp. 275285, 2012. 
* Y. Matsuyama, R. Yokote, Y. Yokosawa, Conversion of sensitivitybased tasks from brain signals and motions: Applications to humanoid operation, Proc. IASTED Int. Conf. on Artificial Intelligence, pp. 271277, 2012. 
* Y. Matsuyama and R. Yokote, From convex divergence to humanaware 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 alphaEM algorithm: Discrete and continuous alphaHMMs, Proc. of International Joint Conference on Neural Networks, pp. 809816, San Jose, CA, 2011. 
* R. Yokote, T. Nakamura and Y. Matsuyama, Independent component analysis with graphical correlation: Applications to multivision coding, Proceedings of International Joint Conference on Neural Networks, San Jose, CA, pp. 701708, 2011. 
* Y. Matsuyama, R. Hayashi and R. Yokote, Fast estimation of hidden Markov models via alphaEM algorithm, Proc. of 2011 IEEE Statistical Signal Processing Workshop, Nice, France, pp. 8992, 2011. 
* Y. Matsuyama Bioinformatics in silico, Baifukan Pub. Co. Tokyo, 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. 101111, 2010. 
* Y. Matsuyama and R. Hayashi, AlphaEM gives fast hidden Markov model estimation: Derivation and evaluation of alphaHMM, Proc. Int. Joint Conf. on Neural Networks, pp. 663670, 2010. 
* R. Yokote and Y. Matsuyama, Yet rapid ICA: Applications to unindexed imagetoimage retrieval, Proc. Int. Joint Conf. on Neural Networks, pp. 42554262, 2010. 
Biosignal integration for humanoid operation: Gesture and brain signal recognition by HMM/SVMembedded BN, Lecture Notes in Computer Science, No. 5506, pp. 351359, 2009. 
* T. Kato, S. Honma, Y. Matsuyama, T. Yoshino and Y. Hoshino, Sensibilityaware image retrieval using computationally learned bases: RIM, JPG, J2K and their mixtures, Lecture Notes in Computer Science, No. 5506, pp. 620627, 2009. 
* M. Takata and Y. Matsuyama, Protein folding classification by committee SVM array, Lecture Notes in Computer Science, No. 5507, pp. 369377, 2009. 
* Y. Matsuyama, F. Matsushima, Y. Nishida, T. Hatakeyama, N. Ochiai and S. Aida, Multimodal belief integration by HMM/SVMembedded Bayesian network: Applications to ambulating PC operation by body motions and brain signals, Lecture Notes in Computer Science, No. 5768, pp. 767778, 2009. 
* Y. Matsuyama and Y. Nishida, HMMembedded Bayesian network for heterogeneous command integration: Applications to biped humanoid operation over the network, Proc. CSTST 2008, pp.138145, 2008. 
* Y. Matsuyama, F. Ohashi, F. Horiike, T. Nakamura, S. Honma, N. Katsumata, and Y. Hoshino, Imagetoimage 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. 5156, 2006. 
* N. Katsumata, Y. Matsuyama, T. Chikagawa, F. Ohashi, F. Horiike, S. Honma and T. Nakamura, Retrievalaware image compression, its format and viewer based upon learned bases, Lecture Notes in Computer Science, No. 4233, pp. 420429, 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. 
* D. Kawakita, K. Hosaki and Y. Matsuyama, Turbo encoder and decoder using fakeprocess interleaver, 8th LSI IP Award, design specification document, 2006. 
* Y. Matsuyama, T. Shiga, T. Chikagawa, N. Takahashi and Y. Ueda, Network communication strategies for cooperative physical agents, Proceedings of AsiaPacific Symposium on Information and Telecommunication Technologies, Vol. 1, pp. 148153, 2005. 
* Y. Matsuyama, Y. Ito, K. Onuki and Y. Ishihara, Decomposition of Discretesymbol biosequences to hidden components: Independent component analysis for DNA promoter recognition, Proceedings of International Conference on Neural Information Processing, Vol. 1, pp. 538543, 2005. 
* N. Katsumata and Y. Matsuyama, Database retrieval for similar images using ICA and PCA bases, Engineering Applications of Artificial Intelligence, Vol. 18, pp. 705717, 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. 11351141, 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. 686691, 2004. 
* Y. Matsuyama, H. Kataoka, N. Katsumata and K. Shimoda, ICA photographic encoding gear: Image bases towards IPEG, Proc. IJCNN, vol. 3, pp. 21292134, 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. AsiaPacific Symposium on Information and Telecommunication Technologies, Proc. AsiaPaific Symposium on Information and Telecommunication Technologies, Vol. 1, pp. 6368, 2003. 
* Y. Matsuyama, N. Katsumata and R. Kawamura, Independent component analysis minimizing convex divergence, Lecture Notes in Computer Science, Springer Verlag, No. 2714, pp. 2734, 2003. 
* Y. Matsuyama, The alphaEM algorithm: Surrogate likelihood maximization using alphalogarithmic information measures, IEEE Trans. on Information Theory, Vol. 49, pp. 692706, 2003. 
* Y. Matsuyama, S. Imahara and N. Katsumata, Optimization transfer for computational learning: A hierarchy from fICA and alphaEM to their offsprings, Proceedings of International Joint Conference on Neural Networks, Vol. 3, pp. 18831888, 2002. 
* Y. Matsuyama, N. Katsumata, Y. Suzuki and S. Imahara, The alphaICA algorithm, Proceedings of Independent Component Analysis and Blind Signal Separation, pp. 297302, 2000. 
* Y. Matsuyama TheαEM algorithm and its basic properties, Trans IEICE, Vol. J82DI，pp. 13471358, 1999． 
* Y. Matsuyama, Multiple descent cost competition: Restorable selforganization and multimedia information processing, IEEE Trans. on Neural Networks，Vol. 7，pp. 652668, 1998. (Outstanding Paper Award of IEEE Trans. NN, 2001 
* S. Okamoto, Y. Matsuyama and K. Oshima, Computer Dictionary，Kyoritsu Pup. Co, Tokyo，1997． 
* Y. Matsuyama, The alphaEM Algorithm: A block connectable generalized learning tool for neural networks, Lecture Notes in Computer Science, Springer Verlag, No. 1240, pp. 1240，483492, 1997. 
* Y. Matsuyama, Harmonic competition: A selforganizing multiple criteria optimization, IEEE Trans. on Neural Networks，Vol. 7，pp. 652668, 1996. 
* Y. Matsuyama, Competitive learning among massively parallel agents: Applications to traveling salesperson problems, Neural, Parallel & Scientific Computations, Vol. 1, pp. 181197, 1993. 
* Y. Matsuyama and T. Tomizawa, Introduction to VLSI Design, Kyoritsu Pub. Co., Tokyo, 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. COM30, pp. 711720, 1982. 
* Y. Matsuyama and R. M. Gray, Universal tree encoding for speech, IEEE Trans. Information Theory, Vol. IT27, pp. 3140, 1981. 
* 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. ASSP24, pp. 367376, 1980. 
* Y. Matsuyama, Mismatch robustness of linear prediction and its relationship to coding, Information and Control (Information and Computation), Vol. 47. pp. 237262, 1980. （IEEE Fellow Award対象論文，1998） 
* 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. 139145, 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. 127145, 1974. 
* Y. Matsuyama, Studies on stochastic modeling of neurons, Dr. Engineering Dissertation, Waseda University, Mar., 1974. 
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