Naonori Ueda

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Naonori Ueda
Senior Distinguished Scientist / Director, Machine Learning・Data Science Center
PhD
NTT CS-Labs.

Biography

Naonori Ueda received the B.S., M.S., and Ph D degrees in Communication Engineering from Osaka University, Osaka, Japan, in 1982, 1984, and 1992, respectively. In 1984, he joined the Electrical Communication Laboratories, NTT, Japan, where he was engaged in research on image processing, pattern recognition, and computer vision. In 1991, he joined the NTT Communication Science Laboratories, where he has invented a significant learning principle for optimal vector quantizer design and has developed some novel learning algorithms including deterministic annealing EM (DAEM) algorithm, ensemble learning, the split and merge EM (SMEM) algorithm, semi-supervised learning, variational Bayesian model search algorithm for mixture models and its application to speech recognition, and probabilistic generative models (PMM) for multi-labeled text in WWW. His current research interests include parametric and non-parametric Bayesian approach to machine learning, pattern recognition, data mining, signal processing, and cyber-physical systems. From 1993 to 1994, he was a visiting scholar at Purdue University, West Lafayette, USA. He was a director of NTT Communication Science Laboratories(April,2010-March,2013). Currently, he is a director of Machine Learning and Data Science Center. He was an associate editor of Neurocomputing (2007-2012) and Journal of Neural Networks(2003-2010). He is a sub-project leader, Funding Program for World-Leading Innovative R&D on Science and Technology (First Program), Cabinet Office, Government of Japan, March (2010-2014). He is a member of the Infomation Processing Society of Japan(IPSJ), a fellow of the Institute of Electronics, Information, and Communication Engineers in Japan(IEICE), and a senior member of IEEE.

Awards

SIGKDD Best Research Paper Award Honorable Mention, 2010
Best Paper Award, ICONIP (International Conference on Neural Information Processing), 2009
Best Paper Award, IPS (Information Processing Society), 2009
Best Paper Award, Funai Foundation Award, 2007
Telecommunication Advanced Foundation Award, 2005
Yamashita SIG Research Award, IPS (Information Processing Society), 2005
Paper Award, Funai Foundation Award, 2005
Research Award, JSAI (Japanese Society for Artificial Intelligence), 2005
Meritorious Award, IEICE (Institute of Electronics, Information, and Communication Engineers), 2004
Best Paper Award, Funai Foundation Award, 2004
Best Paper Award, IEICE (Institute of Electronics, Information, and Communication Engineers), 2004
Research Award, JNNS(Japanese Neural Network Society), 2003
Best Paper Award, IEICE (Institute of Electronics, Information, and Communication Engineers), 2000
Telecommunication Advanced Foundation Award, 1997
Research Award, JNNS (Japanese Neural Network Society), 1995

Professional Activities

Member of the Education Council, Unit of Design, Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, June 2013-present.
Off-campus Program Member, Collaborative Graduate Program in Design, Kyoto University Design School, 2013-present
Reserch Area Adviser, JST Strategic Basic Research Programs, June 2013-present.
* Research Area: Advanced Core Technologies for Big Data Integration
* JST:Japan Science and Technology Agency
Member of the Advisory Council for Science and Technology, MEXT, February 2013-present.
Vice Chair, IEEE Kansai section, January 2013-present..
Member, ISM Steering Committee of the Cooperation with Mathematics Program, December 2012-present.
* ISM: The Institute of Statistical Mathematics
Sub-Project Leader, Funding Program for World-Leading Innovative R&D on Science and Technology (First Program),
Cabinet Office, Government of Japan, March 2010-present.
Principal Investigator, Scientific Research (C), MEXT, Government of Japan, April 2008-March 2011.
* MEXT: Ministry of Education, Culture, Sports, Science and Technology
Program committee, Technical Committee, MPS, IPS 2006-March 2010.
* IPS : Information Processing Society
* MPS: Mathematical Modeling and Problem Solving
Associate Editor, Neurocomputing Journal, 2004-present.
Associate Editor, Neural Networks Journal, 2003-2010.
Part-time Researcher, RIKEN, The Institute of Physical and Chemical Research, 2003-September 2012.
Visiting Collaborated Research, Hinton Lab., University of College London, UK, April 1999, August 2000.
Visiting Collaborated Research, Hinton Lab., University of Toronto, CANADA, October 1997.
Visiting Scholar, Purdue University, USA, 1993-1994.
Senior Program Committee, ICML, 2007.
* ICML: International Conference on Machine Learning
General Conference Board, JNNS, 2001.
Board Member, JNNS, 2000-2001.
* JNNS: Japanese Neural Network Society
General Chair, IBIS, 2003.
Program Commitee, IBIS Workshop, 2000.
Fellow, IEICE, 2009
General Chair, IBIS Technical Group, IEICE, 2003-2004.
* IBIS: Information-Based Induction Sciences and Machine Learning
Editor in Chief, IEICE Transactions on Infomation and System (Special Issue on IBIS), 2001.
Paper Editorial Committee Member, IEICE, 1999-2002.
Special Issue, Editorial board, IEICE, 1998, 2002-2003.
Paper Review Member, IEICE, 1996-present.
Editorial board, IEICE, 1996-1998.
* IEICE: The institute of Electronics, Information,and Communication Engineers
Program Committee (Research), ACM SIG-KDD, 2010-present.
* ACM: Association for Computing Machinery
Paper Review Member, NIPS, 1999-2002. 2005-present
* NIPS: Neural Information Processing Systems
Program Committee, IEEE NNSP, 2001-2002.
* NNSP: Neural Networks for Signal Processing
Paper Review Member, IEE, 1997-2000.
* IEE: The institute of Electrical Engineers
Commitee Member, AVIRG, 1992-1993.
* AVIRG: Audio and Visual Information Research Group

Invited Academic Talks

"Machine Learning for Big Data Analysis -current work and future vision-", AY2013 Academic Lecture of Institute of Science and Engineering, Ritsumeikan University, December 16, 2013.
"Bayesian Meta-ｌearning and its Application to High-Level Real Nursing Activity Recognition Using Accelerometers", Forum "Math-for-Industry" 2013, November 5, 2013.
"Basics of Bayesian Modeling in Machine Learning", MLMI 2013, A MICCAI 2013 Workshop, September 22, 2013.
"Machine Learning Technology for Creating New Value from Big Data", Symposium 2013, Graduate School and Faculty of Information Science and Electrical Engineering, Kyusyu University, May 14, 2013.
"Statistical Machine Learning Techniques for The Era of Big Data", IMI Colloquium, Kyusyu University, January 16, 2013.
"Bayesian Relational Data Analysis", KDD2012, Beijing, August 14, 2012.
"Statistical Machine Learning Techniques for the Era of Big Data", MIRU2012, Fukuoka International Congress Center, August 7, 2012.
"New Developments on Machine Learning Techniques", DCP Business Seeds Workshop for Digital Information Appliance Industry, Kansai Institute of Information Systems,July 2012.
"Statistical Machine Learning Techniques for Big Data analysis", Toyota Central R&D LABS.,INC., July 2012.
"The Era of Big Data: New Developments on Information Science", Osaka University School of Engineering, July 2012.
"Bayesian Relational Data Analysis", Mext Workshop Cryptographic Technologies suitable for Cloud Computing, The Institute of Statistical Mathematics, February 2012.
"Arrival of the Era of Big Data", IEEE Kansai Section Lecture Meeting, TKP Honmachi Business Center, Osaka, January 2012.
"Machine Learning for Pattern Recognition", IBISML Tutorial, Tokyo University, January 2012.
"Business Challenges for the 21st Century", Academic Center for Computing and Media Studies, Kyoto University, November 2011.
"Introduction to Statistical Machine Learning", NII Karuizawa Saturday Salon, International Seminar House For Advanced Studies, November 2011.
"Statistical Machine Learning for Intelligent Computing" IPSJ SIGMUS, October, 2010.
"Introduction to Nonparametric Bayesian Models," IPSJ CVIM/IEICE PRMU, March 2009.
"Nonparametric Bayesian Learning," NHK Science and Technical Research Labs, August 2007.
"Inference Methods for Nonparametric Bayes models, Workshop on Bayesian Inference," (The Institute of Statistical Mathematics), August. 2007.
"Multimedia Signal Processing," Osaka University, May 2007.
"Nonparametric Bayesian Theory and its Application to Data Mining," SIG-DMSM, July 2006.
"Mathematical MOodeling for Multiple Topics," Information ProcessingSociety of Japan (IPSJ), Yamashita SIG Award Memorial Lecture, March 2006
"Ensemble Learning," IEICE PRMU, September 2004.
"New Development of Text Modeling," NLP, March 2003.
"Variational Bayes/Parametric Mixture Models," ATR Spoken Language Translation Research Laboratories, July 2002.
"Ensemble Learning," The Institute of Systems, Control, and Information Engineers, May 2002.
"New Development of the EM Algorithm. -Variational Bayes- ," Meeting of Technical Group on Neural Computation, IEICE, January 2002.
"Theory and Applications of Variatiaonal Bayes," The Institute of Statistical Mathematics, February 2001.
"New Development of the EM Algorithm," Japanese Society of Computational Statistics, October 2000.
"The Front of Statistical Learning Theory," Kyoto University, April 2000.
"Optimal Model Search based on Bayesian Approach," Biometric Analysis Dept., SHIONOGI & CO., LTD, March 2000.
"Latent Variable Models and Probabilistic Dimensionality Reduction," The Institute of Statistical Mathematics, September 1998.
"A Feature Extraction Method Based on Latent Variable Models," Meeting of Technical Group on Pattern Recognition and Media Understanding, IEICE, June 1998.
"Probabilistic Neural Networks Based on Latent Variable Models," Yukawa Institute for Theoretical Physics, Kyoto University, January 1998.
"Mathematical Morphology," Meeting of Technical Group on Precision Engineering, August 1996.
"EM Algorithm," Bio-infomatics Research Meeting, October 1995.
"Deterministic Annealing EM Algorithm," ATR Interpreting Telecommunications Research Laboratories, May 1995.
"Deterministic Annealing EM Algorithm," GA Research Meeting, April 1995.
"Ensemble Learning," Osaka University, January 1995.

Career

Part-time Lecturer, (Graduate School of Informatics, Kyoto University, Bayesian Learning & Data Mining), 2010
Part-time Lecturer, (Yamagata University, Advanced machine learning), 2010
Part-time Lecturer, (Tokyo University, Bayesian Learning Theory), 2007
Guest Professor, (Nara Advanced Institute of Science and Technology (NAIST), 2004-2013.
Guest Associate Professor, (Nara Advanced Institute of Science and Technology (NAIST), 1998-2004
Part-time Lecturer, (Osaka University), 2003-2011.
Part-time Lecturer, (Kyoto University, Pattern Recognition and Bayesian Learning), 2003-present.
Part-time Lecturer, (Waseda University, Statistical Learning Theory), 2003.
Part-time Lecturer, (Okayama University, Statistical Pattern Recognition), 1999.
Part-time Lecturer, (Nagoya Institute of Technology, Electrical and Computer Enginnering), 2002.
Part-time Lecturer, (Tsukuba University, Statistical Learning Theory), 1999-2002.

Publications

Referｒed Journal Papers

Sun, X., Kashima, H. and Ueda, N., "Large-Scale Personalized Human Activity Recognition using Online Multi-Task Learning" IEEE Transactions on Knowledge and Data Engineering (TKDE), (accepted 2012).
Iwata, T., Yamada, T., SakuraI, Y. and Ueda, N., "Sequential Modeling of Topics Dynamics with Multiple Timiscales ", ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 5 Issue 4, 19:1-19:27, 2012.
Fujino, A., Ueda, N. and Nagata, M., "Robust semisupervised learning for data selection bias", Transaction of Information Processing Society of Japan, Vo.4, No.2, pp. 31-42, 2011 (in Japanese).
Hachiya, H., Sugiyama, M. and Ueda, N., "Importance-weighted least-squares probabilistic classifier for covariate shift adaptation with application to human activity recognition", Neurocomputing, (accepted).
Iwata, T., Tanaka, T., Yamada, T. and Ueda, N., " 　Improving Classifier Performance Using Data with Different Taxonomies", 　IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.23, No.11, 1668-1677, 2011.
Fujino, A., Ueda, N. and Nagata, M., "Robust Semi-supervised Learning for Labeled Data Selection Bias", Transaction of Information Processing Society of Japan, Vol.2010-MPS-80 No.8, 2010, (in Japanese).
Fujino, A., Ueda, N. and Nagata, M., "Robust semisupervised learning for data selection bias", Transaction of Information Processing Society of Japan, Vol.2010-MPS-80 No.8, 2010, (in Japanese).
Ishiguro, K., Iwata, T., and Ueda, N.,"Dynamic Infinite Relational Model for Time-varying Relational Data Analysis", Transaction of Information Processing Society of Japan, Vol.3, No.1, 1-12, 2010, (in Japanese).
Iwata, T., Watanabe, S., Yamada, T., and Ueda, N., "Topic Tracking Model for Purchase Behavior Analysis", Transactions of IEICEJ, Vol.J93-D, No.6, pp.978-987, 2010, (in Japanese).
Iwata, T., Tanaka, T., Yamada, T., and Ueda, N. , " Improving Classifier Performance using Data with Different Taxonomies", IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear.[IEEE Xplore] [DOI link] [IEEE Copyright Notice], 2010.
Iwata, T., Tanaka, T., Yamada, T., and Ueda, N., "Model Learning when Distributions Differ over Time", Transactions of IEICEJ, Vol.J92-D, No.3, 361-370, 2009, (in Japanese).
Iwata, T., Yamada, T., and Ueda, N., "Visualizing Documents based on Topic Models",Journal of Information Processing Society of Japan, Vol.50, No.6,1649-1659, 2009, (in Japanese).
Kawamae, N., Sakano, H., Yamada, T., and Ueda, N.,"Collaborative filtering focusing on the dynamics and precedence of user preference",Transactions of IEICEJ, (D-II), Vol. J92-DII, No.6, pp. 767-776, 2009, (in Japanese).
Fujino, A., Ueda, N., and Saito, K., " Semisupervised learning for a hybrid generative/discriminative classifier based on the maximum entropy principle", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 30(3), 424-437,2008. [IEEE Xplore] [DOI link] [IEEE Copyright Notice]
Ueda, N., Yamada, T., and Kuwata, S., "Co-clustering Discrete Data Based on the Dirichlet Process Mixture Model", Transaction of Information Processing Society of Japan, Vol.1 No.1 (pp. 60-73), 2008, [Transaction of Information Processing Society of Japan],(in Japanese).
Iwata, T., Yamada, T., and Ueda, N., "Collaborative filtering efficiently using purchase orders", Transaction of Information Processing Society of Japan, Vo.49, No.SIG4 (TOM20), pp. 125-134, 2008, (in Japanese).
Naud, A., Usui, S., Ueda, N., and Taniguchi. T., "Visualization of documents and concepts in Neuroinformatics with the 3D-SE Viewer", Neuroinformatics, 2007.
Kuwata, S., and Ueda, N., "One-shot Collaborative Filtering", Transaction of Information Processing Society of Japan, Vol.48, No.SIG_15(TOM_18), pp. 153-162, 2007, [Transaction of Information Processing Society of Japan], (in Japanese).
Kawamae, N., Yamada, T., and Ueda, N., "Personalized Ranking by Identifying, RelativeInnovators", FIT2007 Letters, Vol.6, pp.99-102, 2007.
Kuwata, S., and Ueda, N., "An efficient collaborative filtering algorithm based on marginal rating distributions",International Journal of IT & IC, IEEE CIS, Vol.2, No.1, 2007.
Fujino, A., Ueda, N., and Saito, K., "Semi-supervised Learning of Multi-class Classifiers for Multi-component Data", Transaction of Information Processing Society of Japan, Vol.48, No.SIG_15(TOM_18), pp. 163-175, 2007, [Transactions of IPSJ.], (in Japanese)
Fujino, A., Ueda, N., and Saito, K., "A hybrid generative/discriminative approach to text classification with additional information", Information Processing & Management, Elisevier, Vol.43, pp. 379-392, 2007.
Usui, S., Plames, P., Nagata, K., Taniguchi, T., and Ueda, N., "Keyword extraction, ranking, and organization for the neuroinfomatics platform", Biosystems, Elsevier Science, Vol.88, Issue 3, pp. 334-342, 2007, [Biosystems].
Iwata, T., Saito, K., Ueda, N., Stromsten, S., Griffiths, T., and Tenenbaum, J., "Parametric Embedding for Class Visualization", Neural Computation Vol. 19, No. 9, pp. 2536-2556: 2536-2556, 2007.
Kawamae, N., Yamada, T., and Ueda, N., "Personalized Ranking by Identifying, RelativeInnovators", FIT2007 Letters, Vol.6, pp.99-102, 2007.
Ueda, N. and Yamada, T., "Nonparametric Bayes", Journal of Japanese Applied Mathematics Vol.17, No.3, pp.196-214, 2007.
Fujino A., Ueda, N., and Saito, K., "Text Classification by Effectively Using Additional Information Based on Maximum Entropy Principle(Information Retrieval)", Transaction of Information Processing Society of Japan, Vol.47, No.10, pp. 2929-2937, 2006, [ Transactions of IPSJ.], (in Japanese).
Fujino, A., Ueda, N., and Saito, K., "A hybrid generative/discriminative classifier design for semi-supervised learning", Journal of JSAI，Vol.21, No.3, pp.301-309, 2006, (in Japanese).
Kimura, M., Saito, K., and Ueda, N., "Modeling network growth with directional attachment and communities", Systems and Computers in Japan, Vol. 35, No. 8, pp. 1-11, 2004, [Systems and Computers in Japan].
Ueda, N. and Saito, K., "Parametric mixture models for multi-topic text," Systems and Computers in Japan, Vol.37, No.2, pp. 56-66, 2006, [Systems and Computers in Japan]
Ueda, N., "Ensemble Learning," Transactions of IPSJ, CVIM-1036, (invited) Vol.46, No.SIG15(CVIM 12), pp. 11-20, 2005, [Transaction of Information Processing Society of Japan], (in Japanese)
Iwata, T., Saito, K., Ueda, N., Stromsten, S., Griffiths, T., and Tenenbaum, J., "Parametric Embedding for Class Visualization ", Neural Computation, vol.46,no.9, pp. 2337-2346, 2005, (in Japanese).
Fujino, A., Ueda, N., and Saito, K., "Semi-supervised learning on hybrid generative/discriminative models", FIT2005 Letters, 2005, (in Japanese).
Iwata, T., Saito, K., and Ueda, N., "Visualization via posterior preserving embedding ",FIT2004 Letters, Vol. 3, pp. 119-120, 2004, (in Japanese).
Kaneda, Y., Saito, K., and Ueda, N., "Automatic extraction of correspondences between document taxonomies", FIT2004 Letters, Vol. 3, pp.121-122, 2004, (in Japanese).
Kaneda, Y. and Ueda, N., "A Robust text data clustering method for high-dimensional data", FIT2004 Letters, Vol. 3, pp. 123-124, 2004, (in Japanese).
Fujino, A., Ueda, N., and Saito, K., "Relevance feedback with cross validation", FIT2004, Vol. 3, pp. 53-54, 2004, (in Japanese).
Kimura, M., Saito, K., and Ueda, N., "Modeling share dynamics by extracting competition structure", Physica D, Vol.198, pp. 51-73, 2004.
Watanabe, S., Minami, Y., Nakamura, A., and Ueda, N., "Variational Bayesian Estimation and Clustering for Speech Recognition", IEEE transaction on Speech and Audio Processing, Vol. 12, pp. 365-381, 2004.
Ueda, N., and Inoue, M., "Extended Tied-Mixture HMMs for Both Labeled and Unlabeled Time Series Data", Journal of VLSI Signal Processing, pp. 189-197, 2004.
Kimura, M., Saito, K., and Ueda, N., "Modeling of growing networks with directional attachment and communities", Neural Networks, Vol. 17, No. 7, pp. 975-988, 2004.
Ueda, N., and Saito, K., " Parametric Mixture Models for Multi-Topic Text", Transactions of IEICEJ, (D-II), Vol. J87-DII, No.3, pp. 872-883, 2004, (in Japanese)
Ueda, N. and Inoue, M., "Extended tied-mixture HMMs for both labeled and unlabeled time series data", to appear Journal of VLSI Signal Processing Systems,Vol. 37, pp. 189-197, 2004.
Kimura, M., Saito, K., and Ueda, N., "Modeling of growing networks with directional attachment and communities", Transactions of IEICEJ, Vol. J86-DII, No, 10, pp. 1468-1479, 2003, (in Japanese).
Ueda, N. and Saito, K., "Multi - topic Text Model for Topic - based Text Retrieval", Transaction of Information Processing Society of Japan Vol. 44, No. SIG14(TOM9), pp. 1-8, 2003,[Transaction of Information Processing Society of Japan] (in Japanese).
Yamada, T., Saito, K., and Ueda, N., "Embedding networks data based on cross-entropy minimization", Transaction of Information Processing Society of Japan Vol. 44, No. 9, pp. 2401-2408, 2003, [Transaction of Information Processing Society of Japan] (in Japanese).
Inoue, M. and Ueda, N., "Exploitation of unlabeled sequences in hidden markov models", IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI), Vol. 25, No. 12, pp1570-1581, 2003.
Watanabe, S., Minami, Y., Nakamura, A., and Ueda, N., "Selection of Shared-States Hidden Markov Model Structure Using Bayesian Criterion,", Transactions of IEICEJ, Vol. J86-DII, No. 6, pp. 776-786, 2003, (in Japanese).
Ueda, N. and Ghahramani, Z., "Bayesian model search for mixture models based on optimizing variational bounds", Neural Networks, Vol.15, pp. 1223-1241, 2002.
Inoue, M. and Ueda, N., "Use of Unlabeled Time Series Data in Hidden Markov Models", Transactions of IEICEJ, Vol. J86-DII, No. 2, pp. 173-183, 2003 (in Japanese).
Ueda, N., " Variational Bayesian Learning for Optimal Model Search", Journal of Japanese Society for Artificial Intelligence, Vol.16, No.2, 2001, (in Japanese).
Suzuki, S. and Ueda, N., "Adaptive clustering method using modular learning architecture", Transactions of IEICEJ, Vol. J83_DII, No. 6, pp. 1529-1538, 2000, (in Japanese).
Ueda, N., "EM algorithm with split and merge operations for mixture models (invited)", Transactions of IEICE, Vol. E83-D, No. 12, pp. 2047-2055, 2000.
Suzuki, S., and Ueda, N., "Adaptive clustering method using modular learning architecture", Transactions of IEICEJ, Vol. J83_DII, No. 6, pp. 1529-1538, 2000, (in Japanese).
Ueda, N., Nakano, R., Ghahramani, Z., and Hinton, G. E., "SMEM Algorithm for Mixture Models", Neural Computation, Vol. 12, No. 9, pp. 2109-2128, 2000.
Ueda, N., Nakano, R., Ghahramani, Z., and Hinton, G. E..,"Split and merge EM algorithm for improving Gaussian mixture density estimates (invited)", Journal of VLSI Signal Processing, Vol. 26, pp. 133-140, 2000.
Ueda, N., "Optimal Linear Combination of Neural Networks for Improving Classification Performance", IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI). Vol. 22, No.2, pp. 207-215, 2000.
Ueda, N. and Nakano, R., "Probabilistic Mixture Subspace Method", Transactions of IEICE, Transactions of IEICEJ, Vol. J82-DII, No. 12, pp. 2394-2401, 1999, (in Japanese).
Ueda, N. and Nakano, R., "EM Algorithm with Split and Merge Operations for Mixture Models", Transactions of IEICE, Transactions of IEICEJ, Vol. J82-DII, No. 5, pp. 930-940, 1999, (in Japanese).
Ueda, N., "Optimum Linear Combination of Neural Network Classifiers Based on the Minimum Classification Error Criterion", Transactions of IEICEJ, Vol. J82_DII, No. 3, pp. 522-530, 1999, (in Japanese).
Ueda, N. and Nakano, R., "Deterministic Annealing EM Algorithm", Neural Networks, Vol. 11, No. 2, pp. 271-282, (1998).
Ueda, N. and Nakano, R., "Analysis of Generalization Error on Ensemble Learning", Transactions of IEICEJ, Vol. J80-DII, No. 9, pp. 2512-2521, 1997, (in Japanese).
Ueda, N. and Nakano, R., "Deteministic Anneling EM Algorithm", Transactions of IEICEJ, Vol. J80-DII, No. 1, pp. 267-276, 1997, (in Japanese).
Ueda, N. and Mase, K., "Tracking Moving Contours Using Energy-minimizing Elastic Contour Models", International Journal of Pattern Recognition and Artificial Intelligence, Vol. 9, No. 3, pp. 465-484, 1995.
Ueda, N. and Nakano, R., "A New Competitive Learning Approach Based on an Equidistortion Principle for Designing Optimal Vector Quantizers", Neural Networks, Vol.7, No.8, pp. 1211-1227, 1994.
Ueda, N. and Nakano, R., "Competitive and Selective Learning method for Vector Quantizer Design - Equidistortion Principle and Its Algorithm -", Transactions of IEICEJ, Vol. J77-DII, No. 11, pp. 2265-2278, 1994, (in Japanese).
Ueda, N. and Suzuki, S., "Learning Visual Models from Shape Contours Using Multiscale Convex/Concave Structure Matching", IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 15, No. 4, pp. 337-352, 1993, [ IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI).
Suzuki, S., Ueda, N. and Sklansky, J., "Graph-Based Thinning for Binary Images", International Journal of Pattern Recognition and Artificial Intelligence, Vol. 7, No. 5 pp. 1009-1030, 1993.
Ueda, N., Mase K., and Suenaga Y., "A Contour Tracking Method Using Elastic Contour Model and Energy Minimization Approach", Transactions of IEICEJ, Vol. J75-DII, No. 1, pp. 111-120, 1992, (in Japanese).
Ueda, N. and Suzuki, S., "Automatic Shape Model Acquisition Based on A Generalization of Convex/Concave Structure", Transactions of IEICEJ, Vol. J74-DII, No. 2, pp. 220-229, 1991, (in Japanese).
Ueda, N. and Suzuki, S., "A Deformed Line-Drawing Matching Algorithm Using Multiscale Convex/Concave Structures", Transactions of IEICEJ, Vol. J73-DII, No. 7, pp. 992-1000, 1990, (in Japanese).
Ueda, N., Nagura, M., Kosugi, M., and Mori, K., "Image Enhancemen Method for Law Quality Drawings", Transactions of the Institute of Television Engineers of Japan, Vol. 42, No. 8, pp. 831-836, 1988, (in Japanese).

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Referｒed International Conference Papers

Ishiguro, K., Ueda, N. and Sawada, H., "Subset Infinite Relational Models", AISTATS 2012, Society for AI and Statistics, 2012.
Sawada, H., Kameoka, H., Araki, S. and Ueda, N., "Efficient Algorithms for Multichannel Extensions of Itakura-Saito Nonnegative Matrix Factorization", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), pp. 261-264, 2012.
Sun, X., Kashima, H., Tomioka, R. and Ueda, N., "Large Scale Real-life Action Recognition Using Conditional Random Fields with Stochastic Training", Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2011.
Sun, X., Kashima, H., Tomioka, R. and Ueda, N., "Online Multi-Task Learning for Personalized Continuous Activity Recognition”, IEEE ICDM 2011.
Sawada, H., Kameoka, H., Araki, S. and Ueda, N., "New Formulations and Efficient Algorithms for Multichannel NMF ”, WASPAA 2011, IEEE Signal Processing Society.
Aoyama, K., Sawada, H., Ueda, N. and Saito, K., "Fast approximate similarity seach based in degree-reduced neighborhood graphs", ACM　SIG-KDD 2011.
Sawada, H., Kameoka, H., Araki, S. and Ueda, N., "Formulations and Algorithms for Multichannel Complex NMF", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2011) , pp. 229-232, May, 2011.
Sun, X., Kashima, H., Tomioka, R. and Ueda, N.,"Large Scale Real-life Action Recognition Using Conditional Random Fields with Stochastic Training", Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Shenzeng, China, 2011. (accepted)
Sun, X., Kashima, H., Matsuzaki, T. and Ueda, N., "A Robust, Accurate, and Fast Stochastic Gradient Training Method for Modeling Latent-Information in Data", IEEE International Conference on Data Mining (ICDM2010), pp.1067-1072, Sydney, Australia, 2010.
Hachiya, H., Sugiyama, M. and Ueda, N., " Coping with new user problems: Transfer learning in accelerometer-based human activity recognition ", NIPS 2010 Workshop on Transfer Learning by Learning Rich Generative Models, 2010.
Fujino, A., Ueda, N. and Nagata, M., "A Robust Semi-supervised Classification Method for Transfer Learning ", ACM Conference on Information and Knowledge Management (CIKM2010), 2010.
Ishiguro, K., Iwata, T., Ueda, N. and Tenenbaum, J. B., " Dynamic Infinite Relational Model for Time-varying Relational Data Analysis ", Advances in Neural Information Processing Systems 23 (NIPS2010), 2010.
Aoyama, K., Watanabe, S., Sawada, H., Minami, Y., Ueda, N. and Saito, K.,"Fast Similarity Search On A Large Speech Data Set With Neighborhood Graph Indexing ", International Conference on Acoustics, Speech, and Signal Processing(ICASSP2010), pp. 5358-5361, 2010.
Usui, S., Kamiji, N. L., Taniguchi, T. and Ueda N., "RAST: A Related Abstract Search Tool", International Conference on Neural Information Processing (ICONIP2009), 2009.
Iwata, T., Yamada, T. and Ueda, N., "Modeling Social Annotation Data with Content Relevance using a Topic Model ", Advances in Neural Information Processing Systems (NIPS2009), 835-843, 2009
Iwata, T., Watanabe, S., Yamada, T. and Ueda, N., "Topic Tracking Model for Analyzing Consumer Purchase Behavior ", Proc. of 21st International Joint Conference on Artificial Intelligence (IJCAI-09), 1427-1432, 2009
Iwata, T., Yamada, T. and Ueda, N., "Probabilistic Latent Semantic Visualization: Topic Model for Visualizing Documents", Proc. of 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Minig (KDD2008), pp.363-371, 2008.
Ishiguro, K., Yamada, T. and Ueda, N., "Simultaneous Clustering and Tracking Unknown Number of Objects", Proc. of the 19th IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR08), pp. 1-8, 2008, [CVPR08]
Usui, S., Naud, A., Ueda, N. and Taniguchi, T., "3D-SE Viewer: A Text Mining Tool based on Bipartite Graph Visualization", 20th International Joint Conference on Neural Networks (IJCNN'07), 2007.
Kuwata, S. and Ueda, N., "One-shot Collaborative Filtering", IEEE CIDM2007, Vol.1, No.1, pp.300-307, 2007.
Fujino, A., Ueda, N. and Saito, K., "Semi-supervized learning for multi-component data classification", to appear in Proc. of International Joint Conference on Areificial Intelligence (IJCAI2007), 2007.
Kuwata, S. and Ueda N., "One-shot collaborative filtering", to appear in Pro. of IEEE Symposium on Compututational Intelligence and Data Mining (CIDM2007), 2007.
Kemp, C., Tenenbaum, J. B., Griffiths, T. L., Yamada, T. and Ueda, N., "Learning systems of concepts with an infinite relational model", Proc. of the 21st National Conference on Artificial Intelligence(AAAI-06), 2006
Iwata, T., Saito, K. and Ueda, N., "Visual nonlinear discriminant analysis for classifier design", Proc. of the 14th European Symposium on Artificial Neural Networks (ESANN2006), pp.283-288, 2006.
Usui, S., Palmes P., Nagata, K., Taniguchi, T. and Ueda, N., "Extracting keywords from research abstracts for the neuroinformatics platform index tree", To appear in Proc. of International Joint Conference on Neural Networks (IJCNN2006), 2006.
Ueda, N., "Bayesian probabilistic models for data partitioning and their applications", Proc. of the 17th International Symposium on Mathematical Theory of Networks and Systems (MTNS2006), 2006.
Saito, K. and Ueda, N., "Filtering Search Engine Spam based on Anomaly Detection Approach", Proc. of the KDD2005 Workshop on Data Mining Methods for Anomaly Detection, pp.62-67, 2005.
Usui, S., Palmes, P., Nagata, K., Taniguchi, T. and Ueda, N., "Relevance keyword extraction, ranking, and organization for the neuroinformatics platform, Proc. of International Conference on Biological Computation," Proc. of BIOCOMP, 2005.
Fujino, A., Ueda, N. and Saito, K., "A Classifier design based on combining multiple components by maximum entropy principle," Proc. of the 2nd Asia Information Retrieval Symposium (AIRS2005), 2005.
Kimura, M., Saito, K. and Ueda, N., "Multinomial PCA for extracting major latent topics from document streams," Proc. of IJCNN, 2005.
Fujino, A., Ueda, N. and Saito, K., "A hybrid generative/discriminative approach to semi-supervised classifier design," Proc. of the 20th National Conference on Artificial Intelligence (AAAI-05), pp. 764-769, 2005.
Inoue, M. and Ueda, N., "Retrieving lightly annotated images using image similarities," ACM Symposium on Applied Computing (SAC), Special Track on Information Access and Retrieval (IAR)Santa Fe, March 14-17, pp.1031-1037, 2005.
Iwata, T., Saito, K., Ueda, N., Stromsten, S., Griffiths, T. L. and Tenenbaum, J. B., "Parametric Embedding for Class Visualization, " Advances in Neural Information Processing Systems 17 (NIPS2004), pp. 617-624, 2005.
Kimura, M., K. Saito and N. Ueda, "Modeling share dynamics by extracting competition structure," Proc. of the 5th International Conference on Complex Systems, p. 72, 2004.
Kaneda, Y., Ueda, N. and Saito, K., "Extended Parametric Mixture Model for Robust Multi-labeled Text Categorization," Proc. of the 8-th International Conference on Knowledge-Based Intelligent Information & Engineering Systems, Vol. 3214 of Lecture Notes in Computer Science, pp. 616-623, 2004.
Ueda, N. and Saito, K., "Simplex mixture models for multi-topic text," In Science of Modeling, ISM Report on Research and Education No.17, The Institute of Statisitical Mathematics, pp. 380-381, 2003.
Kimura, M., Saito, K. and Ueda, N., "Modeling share dynamics by extracting competition structure," In Science of Modeling, ISM Report on Research and Education No.17, The Institute of Statisitical Mathematics, pp.366-367, 2003.
Yamada, T., Saito, K. and Ueda, N., "Cross-entropy based embedding for relational data," International Conference on Machine Learning (ICML2003), pp. 832-839, 2003.
Watanabe, S., Minami, Y., Nakamura, A. and N. Ueda, "Bayesian acoustic modeling for spontaneous speech recognition," IEEE Workshop on Spontaneous Speech Processing and Recognition (SSPR03), pp. 47-50, 2003.
Watanabe, S., Minami, Y., Nakamura, A. and Ueda, N., "Application of variational bayesian estimation and clustering to acoustic model adaptation," IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP03), Vol. 1, pp. 568-571, 2003.
Kimura, M., Saito, K. and Ueda, N., "Modeling of growing networks with directional attachment and communities," European Symposium on Artificial Neural Networks (ESANN03), pp. 15-20, 2003.
Kimura, M., Saito, K. and Ueda, N., "Modeling of growing networks with communities," IEEE International Workshop on Neural Networks for Signal Processing (NNSP2002), pp. 189-198, 2002.
Watanabe, S., Minami, Y., Nakamura, A. and Ueda, N., "An application of variational Bayesian approach to speech recognition," to appear Advances in Neural Information Processing Systems 15(NIPS15), MIT Press, pp. 1261-1268, 2002.
Watanabe, S., Minami, Y., Nakamura, A. and Ueda, N., "Constructing shared-state HMMs based on a Bayesian approach," International Conference on Spoken Language Processing (ICSLP02), Vol. 4, pp. 2669-2672, 2002.
Ueda, N. and Saito, K., "Parametric mixture models for multi-topic text," Neural Information Processing Systems 15(NIPS15), MIT Press, pp. 737-744, 2002.
Ueda, N. and Saito, K., "Singleshot detection of multi-category text using parametric mixture models," ACM SIG Knowledge Discovery and Data Mining (SIGKDD2002), pp. 626-631, 2002.
Inoue, M. and Ueda, N., " HMMs for both labeled and unlabed time series data," IEEE Neural Networks for Signal Processing (NNSP2001), pp. 93-102, 2001.
Ueda, N. and Ghahramani, Z., "Optimal model inference for Baysian mixture of experts," IEEE Neural Networks for Signal Processing (NNSP2000), pp. 145-154, 2000.
Ueda, N., Nakano, R., Ghahramani, Z. and Hinton, G. E., "Pattern classification using a mixture of factor analyzers," IEEE Neural Networks for Signal Processing (NNSP99), pp. 525-533, 1999.
Ueda, N., Nakano, R., Ghahramani, Z. and Hinton, G. E., "SMEM algorithm for mixture models," Neural Information Processing Systems 11 (NIPS11), pp. 599-605, 1999.
Ueda, N., Nakano, R., Ghahramani, Z. and Hinton, G. E., "Split and merge EM algorithm for improving Gaussian mixture density estimates," IEEE Neural Networks for Signal Processing (NNSP98), pp. 274-283, 1998.
Ueda, N. and Nakano, R., "Combining discriminant-based classifiers using the minimum classification error discrimininant,"IEEE Neural Networks for Signal Processing (NNSP97), pp. 365-374, 1997.
Suzuki, S. and Ueda, N., "Self-organization of feature columns and its application to object classification," Proceedings of International Conference on Neural Information Processing (ICONIP97), pp. 1166-1169, 1997.
Ueda, N. and Nakano, R, "Generalization error of ensemble estimators," Proceedings of International Conference on Neural Networks (ICNN96), pp. 90-95, 1996.
Ueda, N. and Nakano, R, "Deterministic annealing variant of the EM algorithm," Neural Information Processing Systems 7 (NIPS7), MIT Press, Cambridge MA, pp. 545-552, 1995.
Ueda, N. and Nakano, R, "A new maximum likelihood training and application to probabilistic neural networks," Proceedings of International Conference on Artificial Neural Networks (ICANN95), pp. 497-504, 1995.
Ueda, N. and Nakano, R, "Estimating expected error rates of neural network classifiers in small sample size situations: A comparison of cross-validation and bootstrap," International Conference on Neural Networks (ICNN95), pp. 101-104, 1995.
Ueda, N. and Nakano, R, "Mixture density estimation via EM algorithm with deterministic annealing," Proceedings of IEEE Neural Networks for Signal Processing (NNSP94), pp. 69-77, 1994.
Ueda, N. and Nakano, R, "A new learning approach based on equidistortion principle for optimal vector quantizer Design," Proceedings of IEEE Neural Networks for Signal Processing (NNSP93), pp. 362-371, 1993.
Ueda, N. and Nakano, R, "Competitive and selective learning method for designing optimal vector quantizers," Proceedings of IEEE International Conference on Neural Networks (ICNN93), pp. 1444-1450, 1993.
Ueda, N. and Mase, K., "Tracking moving contours using energy-minimizing elastic contour models,"Proceedings of European Conference on Computer Vision (ECCV92), pp. 453-457, 1992.
Suzuki, S. and Ueda, N., "Robust vectorization using graph-based thnning and reliability-based line approximation," Proceedings of IEEE Conference on Computer Vision (CVPR91), pp. 494-500, 1991.
Ueda, N. and Suzuki, S., "Automatic shape model acquisition using multiscale segment matching," Proceedings of International Conference on Pattern Recognition (ICPR90), pp. 897-902, 1990.
Ogawa, H. Kawada, E. and Ueda, N., "Application of image processing equipment with multiprocessors to line-drawing recognition," Proceedings of SPIE-845, pp. 97-103, 1987.
Okudaira, M. Ueda, N. and Aoki, U., "Image enhancement of handwritten drawings and their recognition followed by interactive processing," Proceedings of SPIE-707, pp. 42-50, 1986.

Invited Paper

Fujino, A., Ueda, N. and Nagata, M., "Adaptive Semi-supervised Leaning in Labeled Data from and Unlabeled　Data from Different Distributions ", Knowledge and Information Systems, Springer , 2011.
Ueda, N., Nakano, R., "Competitive and selective learning method for vector quantizer design -Equidistortion principle and its algorithm," Systems and computers in Japan, Scripta Technica, Inc., Vol. 26, No. 9, pp. 34-49, 1995.
Ueda, N., Mase, K. and Suenaga, Y., "A contour tracking method using elastic contour model and energy minimizing approach," Systems and computers in Japan, Scripta Technica, Inc., Vol. 24, No. 8, pp. 59-70, 1993.
Ueda, N. and Suzuki, S., "Automatic shape model acquisition based on a generalization of convex/concave structure," Systems and computers in Japan, Scripta Technica, Inc. Vol. 23, No. 1, pp. 89-100, 1992.
Ueda, N. and Suzuki, S., "A matching algorithm of deformed planar curves using multiscale convex/concave structures," Systems and computers in Japan, Scripta Technica, Inc. Vol. 22, No. 5, pp. 94-104, 1991.

Invited Tutorial Papers

Ueda, N., "EM algorithm," Society of Instrument and Control Engineers(SICE), Vol.44, No.5, pp.333-338, 2005. (In Japanese)
Ueda, N., "The goal of Web science research," OHM, Vol.91, No.10,pp.6--7, 2004.(In Japanese)
Ueda, N., "Bayesian Inference Algorithms -Approximation Methods for High-Dimensional Integrals-," Journal of the Japanese Society for Artificial Intelligence, Vol. 19, No. 6, 2004 (in Japanese).
Ueda, N. and Saito, K., "Probablistic Models for Multi-topic Text," Information Processing Society of Japan, Vol. 45, No. 2, 3, 2004 (in Japanese).
Ueda, N., "Probablistic Models and Statistical Learning," Computer Today, No.114, 2003.
Ueda, N., "Bayeaian Learning I - IV," Journal of IEICEJ, Vol. 85, No. 4, 6, 7, 8, 2002 (in Japanse).
Ueda, N., "Ensemble Learning," Journal of the Society of Instrument and Control Engineers, Vol. 41, pp. 248, 2002.
Ueda, N., "The Front of Bayesian Learning -Variational Bayesian Learning, " Information Processing Society of Japan, Vol. 42, No. 1, 2001 (in Japanese).
Ueda, N., "An Inquiry into Statistical Learning Research," Information Processing Society of Japan,, Vol. 41, No. 6, pp. 730-733, 2000 (in Japanese).
Ueda, N. and Nakano, R., "Deterministic Annealing EM Algorithm," Journal of the Society of Instrument and Control Engineers, Vol. 38, No. 7, pp. 444-449, 1999 (in Japanse).
Ueda, N. and Nakano, R., "Deterministic Annealing -Another Type of Annealing-," Journal of Japanese Society for Artificial Intelligence, Vol. 12, No. 5, pp. 689-697, 1997 (in Japanse).
Mase, S. and Ueda, N., "Mathematical Morphology and Image Analysis I," Journal of IEICEJ, Vol. 64, No. 2, pp. 166-174 , 1991 (in Japanese).
Ueda, N. and Mase, S., "Mathematical Morphology and Image Analysis II," Journal of IEICEJ, Vol. 64, No. 3, pp. 271-279, 1991 (in Japanse).

Internal Invited Technical Reports at NTT

Fujino, A., Ueda, N., and Saito, K., "Semi-supervised learning forautomatic text classification, " NTT Technical Journal, Vol.19, No.6, pp.26-28, 2007. (In Japanese)
Ueda, N., "Web Science Research," NTT Technical Review, Vol. 3, No. 3, pp. 12-14, 2005.
Ueda, N., "Web Science Research," NTT Technical Journal, Vol.16, No. 6, p. 22, 2004. (In Japanese)
Ueda, N. and Nakano, R., "Competitive and Selective Learning Method for Optimal Vector Quantizer Design," NTT R&D, Vol. 42, No. 6, 1993 (in Japanese).
Nakano, R., Ueda, N., Saito, K., and Yamada, T., " Research on Learning Aiming at Artificial Intelligence," NTT R&D, Vol. 42, No. 9, pp. 1175-1184, 1993 (in Japanese).
Ueda, N., Mase, K., and Suenaga, Y., "Contour Tracking Method Using Energy-minimizing Elastic Models," NTT R&D, Vol. 42, No. 4, pp. 477-486, 1993 (in Japanese).
Ueda, N. and Suzuki, S., "Multiscale Convex/Concave Structure Matching : MC Matching Method," NTT R&D, Vol. 40, No. 3, pp.399-406, 1991 (in Japanese).
Kawada, E., Ueda, N., Ogawa, H., and Kosugi, M., "A Figure Recognition Method for Hand-Written Drawings," NTT Electrical Communications Laboratories Technical Journal, Vol. 37, No. 3, pp. 217-223, 1988 (in Japanese).
Ueda, N., Nagura, M., Hoshino, T., and Mori, K., "Image Enhancement Method for Hand-Written Line Drawings," NTT Electrical Communications Laboratories Technical Journal, Vol. 37, No. 3, pp. 211-216, 1988 (in Japanese).

Book & Book Chapters

Kabashima, Y. and Ueda, N., "Frontier of Statistical Science 11, Computational Statistics I - (3)," Iwanami Shoten, Japan, 2003.(in Japanese)
Ishii, K., Ueda, N., Maeda, E., and Murase, H., "Introduction to Pattern Recognition," Ohm-Sha, Tokyo, Japan, 1998.(in Japanese)
Ueda, N., "Chapter 3: Pattern Recognition Theory," in IEICEJ (Ed.),"Handbook of Electronics, Information and Communication," Asakura-Shoten, Tokyo, Japan, 1998.(in Japanese)
Ueda, N., "Chapter 9: Vector Quantization," in Amari, S. (Ed.),"Handbook of Brain Science," Asakura-Shoten, Tokyo, Japan, 1995.(in Japanese)
NTT Human Interface Laboratory, Project RTV, Japanese translation of "Horn, B. K. P., Robot Vision, MIT-Press, 1986" Asakura-Shoten, Tokyo, Japan, 1993. (in Japanese)

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