Publications
 Journal Papers
 arXiv Papers
 International
Conference Papers
 Invited
Papers & Tutorial Articles
 Internal Invited
Technical Reports at NTT
 Book & Book
Chapters
 Okazaki, T., Morikawa, N., Fujiwara, H., and Ueda, N., "Monotonic
neural network for ground ｍotion predictions to avoid overfitting to
recorded site, " Seismological Research Letters, 2021; https://doi.org/10.1785/0220210099.
 Okawa, M., Owata, T., Kurashima, T., Tanaka, Y., Toda, H., and Ueda, N., "Deep mixture point processes, "
Transaction of the Japanese Society for Artificial Intelligence. 2021.
 Fujiwara, Y., Kanai, S., Ida, Y.,
Kumagai, A., and Ueda, N.,"Fast algorithm for anchor graph hashing,"
Proc. of the VLDB Endowment, Vol.14, Issue 6, 2021.

Tanaka, Y., Iwata、T., Kurashima、T., Ueda. N., Tanaka、T.,"Timedelayed collective flow diffusion models for inferring
latent people flow from aggregated data at limited locations," Artificial
Intelligence, Vol.292, 103430, 2021.
 Kalantar, B., Ueda, N.,Saeidi, V.,Ahmadi, K.,Halin, A.A., and Shabani,
F.,"Landslide susceptibility mapping: Machine and ensemble learning
based on remote sensing big data. Remote Sensing. 2020, 12(11), 1737; https://doi.org/10.3390/rs12111737.
 Takahashi, I, Suzuki, Nao, Yasuda, N., Kimura, A.,
Ueda, N., Tanaka, M., Tominaga, N., Yoshida, N.,"Photometric classification of hyper suprimecam transients using
machine learning," Publications of the Astronomical Society of Japan,
Vol.72, Issue 5, 89,
pp.122, 2020.
 Iwata, T., Toyoda,M., Tora,S., and Ueda,N., "Anomaly Detection
with Inexact Labels," Machine Learning, Vol.109, Issue. 8,
pp.16171633, 2020.

Gibril, M. B. A., Kalantar, B.,
AlRuzouq, R., Ueda, N., Saeidi, V., Shanableh, A., Mansor, S., and Shafri, H.
Z. M., "Mapping heterogeneous urban landscapes from the fusion of digital
surface model and unmanned aerial vehiclebased images using adaptive multiscale
image segmentation and classification," Remote Sensing, 2020,12(7), 1081; https://doi.org/10.3390/rs12071081,
2020.
 Yamamoto, Y., Tsuzuki, T., Akatsuka,
J., Ueki, M., Morikawa, H., Numata, Y., Takahara, T.,
Tsuyuki, T., Shimizu, A., Maeda,
K., Tsuchiya, S., Kanno, H., Kondo, Y., Tamiya, G., Ueda, N.,
and Kimura, G., "Automated acquisition of explainable knowledge from unannotated,"
Nature
Communications, 10,
5642 2019.
 Kalantar, B., AlNajjar, H.A.H., Pradhan, B., Saeidi, V., Halin,
A.A, Ueda, N., Naghibi., S.A.,"Optimized conditioning factors and
machine learning for groundwater potential mapping," Water Journal 2019, 11(9), 1909; https://doi.org/10.3390/w11091909.
 AlNajjar, H. A., Kalantar, B., Pradhan, B., Saeidi, V., Halin,
A. A., Ueda, N., and Mansor, S.,"Land cover classification from fused
DSM and UAV images using convolutional neural networks", Remote
Sensing, 11(12), 1461, 2019.
 Yasuda, N., Tanaka, M., Tominaga, N., Jiang, J., Moriya,
T., Morokuma, T., Suzuki, N., Takahashi, I., Yamaguchi, M., Maeda, K.,
Sako, M., Ikeda, S.,Kimura, A., Morii, M., Ueda, N., Yoshida, N., Lee,
C., Suyu, S., Komiyama, Y., Regnault, N., and Rubin, D., "The Hyper
Suprimecam SSP transient survey in COSMOS: Overview," Publications of
the Astronomical Society of Japan, vol.71, No.4, pp.116, 2019.
 Ueda, N., asd Fujino, A., "Partial auc maximization via nonlinear scoring functions," Xiv submit/2294250, 2018.
 Ueda, N., and Naya, F., "Spatiotemporal multidimensional collective
data analysis for providing comfortable living anytime and anywhere,"
APSIPA Transactions on Signal and Information Processing, Vol.7, No.4,
2018.
 Iwata, T., Hirao, T., Ueda, N.,"Topic models for unsupervised cluster
matching," IEEE Transactions on Knowledge and Data Engineering,
Volume:30, Issue:4, pages 786795, 2018.
 Iwata, T., Shimizu, H., Naya, F. and Ueda, N., "Estimating
people flow from spatiotemporal population data via collective
graphical mixture models," ACM Transactions on Spatial Algorithms and
Systems, Vol. 3, Issue 1, Article 39. 2017.
 Ishiguro, K., Sato, I. and Ueda, N., "Averaged collapsed
variational Bayes inference," Journal of Machine Learning Resaerch
(JMLR), Volume 18, Number 1, pp.129, 2017.
 Ueda,
N., "Proactive Peopleflow Navigation Based on Spatiotemporal
Prediction," Japanese Journal Applied Statistics, Vol.45, No.3,
pp.89104, 2016, (invited).
 Morii, M., Ikeda, S., Tominaga, N., Tanaka, M., Morokuma, T.,
Ishiguro, K., Yamato, J., Ueda, N., Suzuki, N., Yasuda, N. and
Yoshida, N., "Machinelearning selection of optical transients in
Subaru/hyper suprimecam survey," Publication of Astronomical Society
of Japan, Vol.68, No.6, pp.104112, 2016.
 Inoue, S., Ueda, N., Nohara, Y. and Nakashima, N., "Recognizing
and understanding nursing activities for a whole day with a big data
set," Journal of Information Processing, Vol.57, No.10, 2016.
 Ueda, N., "Spatiotemporal prediction and its application to
proactive peopleflow naviation," Journal of the Institute of Image
Electronics Engeneers of Japan (in Japanese), Vol.45, No.1, pp411,
2016.
 Iwata,
T., Hirao T. and Ueda, N., "Unsupervised manytomany object matching via probabilistic
latent variable models," Information Processing & Management, Volume 52, Issue 4, pp682697, July 2016.
 Blondel, M., Onogi, A., Iwata, H. and Ueda, N., "A Ranking Approach
to Genomic Selection," PLOS ONE (peerreviewed open acces journal),
Public Library of Science, 2015.
 Nohara, Y., Kai, E., Ghosh, P., Islam, R., Ahmed, A., Kuroda, M.,
Inoue,
S., Hiramatsu, T., Kimura, M., Shimizu, S., Kobayashi, K., Baba, Y.,
Kashima, H., Tsuda, K., Sugiyama, M., Blondel, M., Ueda, N.,
Kitsuregawa, M. and Nakashima, N., "Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries: Verification Study," Journal of Medical Internet Research, Vol.17, No.1 January 2015.
 Tanaka, Y., Ueda, N. and
Tanaka, T., "Bayesian classifier based on classspecific feature
selection," Transactions of IEICEJ, Vol.J96DDII, No.11, pp.27552764,
2013, (in Japanese).
 Sun, X., Kashima, H. and Ueda, N.,
"LargeScale
Personalized Human Activity Recognition using Online
MultiTask Learning," IEEE Transactions on Knowledge and Data
Engineering (TKDE), Vol.25, No.11, pp.25512563, 2013. [IEEE
Copyright Notice]
 Sawada, H., Kameoka, H., Araki, S. and Ueda,
N., "Multichannel
Extensions of Nonnegative Matrix Factorization with
Complexvalued Data," IEEE Transactions on Audio, Speech, and
Language
Processing, Vol.21, No.5, pp.971982, 2013.[IEEE
Copyright Notice]
 Iwata, T., Yamada, T. and Ueda, N.,
"Modeling
Noisy Annotated Data with Application to Social
Annotation," IEEE Transactions on Knowledge and Data Engineering
(TKDE), Vol.25. No.7, pp.16011613, 2013.[IEEE
Copyright Notice]
 Fujino, A., Ueda, N. and Nagata, M., "Adaptive semisupervised
learning
on labeled and unlabeled data with different distributions," Knowledge
and Information Systems(KAIS), Vol. 37, Issue 1, pp. 129154, Springer,
2013, (invited paper).
 Iwata, T., Yamada, T., Sakurai, Y. and Ueda, N., "Sequential
Modeling of Topics Dynamics with Multiple Timescales," ACM
Transactions on Knowledge Discovery from Data (TKDD), Volume 5
Issue 4,
19:119:27, 2012.
 Hachiya, H., Sugiyama, M. and Ueda, N., "Importanceweighted
leastsquares probabilistic classifier for covariate shift adaptation
with application to human activity recognition," Neurocomputing, Vol.
80, pp 93101, 2012.
 Fujino, A., Ueda, N. and Nagata, M., "Robust Semisupervised
Learning for Labeled Data Selection Bias," Transaction of Information
Processing Society of Japan, Vol.4, No.2, pp. 3142, 2011, (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), Vol.23, No.11,
pp. 16681677, 2011. .[IEEE Xplore] [DOI link] [IEEE
Copyright Notice]
 Fujino, A., Ueda, N. and Nagata, M., "Robust semisupervised
learning for data selection bias," Transaction
of Information
Processing Society of Japan, Vol.2010MPS80 No.8, 2010, (in
Japanese).
 Ishiguro, K., Iwata, T., and Ueda, N.,"Dynamic Infinite
Relational Model for Timedependent Relational Data Analysis," Transaction
of Information Processing Society of Japan, Vol.3, No.1,
112, 2010, (in Japanese).
 Iwata, T., Watanabe, S., Yamada, T., and Ueda, N., "Topic
Tracking Model for Purchase Behavior Analysis," Transactions of IEICEJ,
Vol.J93D, No.6, pp.978987, 2010, (in Japanese).
 Iwata, T., Tanaka, T., Yamada, T., and Ueda, N., "Model Learning
when Distributions Differ over Time," Transactions of IEICEJ,
Vol.J92D, No.3, 361370, 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.6,16491659, 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, (DII),
Vol.
J92DII, No.6, pp. 767776, 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), 424437,2008. [IEEE Xplore] [DOI link] [IEEE
Copyright Notice]
 Ueda, N., Yamada, T., and Kuwata, S., "Coclustering Discrete
Data Based on the Dirichlet Process Mixture Model," Transaction of
Information Processing Society of Japan, Vol.1 No.1 (pp. 6073), 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,
Vol.49, No.SIG4 (TOM20), pp. 125134, 2008, (in Japanese).
 Naud, A., Usui, S., Ueda, N., and Taniguchi. T., "Visualization of documents and concepts in
Neuroinformatics with the 3DSE Viewer," Neuroinformatics, 2007.
 Kuwata, S., and Ueda, N., "Oneshot Collaborative Filtering,"
Transaction of Information Processing Society of Japan, Vol.48,
No.SIG_15(TOM_18), pp. 153162, 2007, [Transaction of Information Processing Society of Japan],
(in Japanese).
 Kawamae, N., Yamada, T., and Ueda, N., "Personalized Ranking by Identifying, Relative
Innovators," FIT2007 Letters, Vol.6, pp.99102, 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., "Semisupervised Learning of
Multiclass Classifiers for Multicomponent Data," Transaction of
Information Processing Society of Japan, Vol.48, No.SIG_15(TOM_18), pp.
163175, 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, Elsevier, Vol.43, No.2, pp. 379392, 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. 334342,
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. 25362556: 25362556, 2007.
 Kawamae, N., Yamada, T., and Ueda, N., "Personalized Ranking by
Identifying, RelativeInnovators," FIT2007 Letters, Vol.6, pp.99102,
2007.
 Ueda, N. and Yamada, T., "Nonparametric Bayes," Journal of
Japanese Applied Mathematics Vol.17, No.3, pp.196214, 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. 29292937, 2006, [ Transactions of IPSJ.], (in Japanese).
 Fujino, A., Ueda, N., and Saito, K., "A hybrid generative/discriminative classifier design
for semisupervised learning," Journal of JSAI，Vol.21, No.3,
pp.301309, 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. 111, 2004, [Systems and Computers in Japan].

Ueda, N. and Saito, K., "Parametric mixture models for
multitopic text," Systems and Computers in Japan, Vol.37, No.2, pp.
5666, 2006, [Systems and Computers in Japan]
 Ueda, N., "Ensemble Learning," Transactions of IPSJ, CVIM1036,
(invited) Vol.46, No.SIG15(CVIM 12), pp. 1120, 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. 23372346, 2005, (in Japanese).
 Fujino, A., Ueda, N., and Saito, K., "Semisupervised 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. 119120, 2004, (in Japanese).
 Kaneda, Y., Saito, K., and Ueda, N., "Automatic extraction of
correspondences between document taxonomies," FIT2004 Letters, Vol. 3,
pp.121122, 2004, (in Japanese).
 Kaneda, Y. and Ueda, N., "A Robust text data clustering method
for highdimensional data," FIT2004 Letters, Vol. 3, pp. 123124, 2004,
(in Japanese).
 Fujino, A., Ueda, N., and Saito, K., "Relevance feedback with
cross validation," FIT2004, Vol. 3, pp. 5354, 2004, (in Japanese).
 Kimura, M., Saito, K., and Ueda, N., "Modeling share dynamics by extracting competition
structure," Physica D, Vol.198, pp. 5173, 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. 365381, 2004.
 Kimura, M., Saito, K., and Ueda, N., "Modeling of growing networks with directional
attachment and communities," Neural Networks, Vol. 17, No. 7, pp.
975988, 2004.
 Ueda, N., and Saito, K., "Parametric Mixture Models for
MultiTopic Text," Transactions of IEICEJ, (DII), Vol. J87DII, No.3,
pp. 872883, 2004, (in Japanese)
 Ueda, N. and Inoue, M., "Extended TiedMixture HMMs for Both
Labeled and Unlabeled Time Series Data," Journal of VLSI
Signal Processing Systems, Vol. 37, pp. 189197, 2004.
 Kimura, M., Saito, K., and Ueda, N., "Modeling of growing
networks with directional attachment and communities," Transactions of
IEICEJ, Vol. J86DII, No, 10, pp. 14681479, 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. 18, 2003, [Transaction of Information Processing Society of Japan]
(in Japanese).
 Yamada, T., Saito, K., and Ueda, N., "Embedding networks data
based on crossentropy minimization," Transaction of Information
Processing Society of Japan Vol. 44, No. 9, pp. 24012408, 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, pp15701581, 2003.
 Watanabe, S., Minami, Y., Nakamura, A., and Ueda, N., "Selection
of SharedStates Hidden Markov Model Structure Using Bayesian
Criterion," Transactions of IEICEJ, Vol. J86DII, No. 6, pp. 776786,
2003, (in Japanese).
 Ueda, N. and Ghahramani, Z., "Bayesian model search for mixture
models based on optimizing variational bounds," Neural Networks,
Vol.15, No.10, pp. 12231241, 2002.
 Inoue, M. and Ueda, N., "Use of Unlabeled Time Series Data in
Hidden Markov Models," Transactions of IEICEJ, Vol. J86DII, No. 2, pp.
173183, 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. 15291538, 2000, (in Japanese).
 Ueda, N., "EM algorithm with split and merge operations for
mixture models (invited)," Transactions of IEICE, Vol. E83D, No. 12,
pp. 20472055, 2000.
 Suzuki, S., and Ueda, N., "Adaptive clustering method using
modular learning architecture," Transactions of IEICEJ, Vol. J83_DII,
No. 6, pp. 15291538, 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.
21092128, 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. 133140,
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. 207215,
2000.
 Ueda, N. and Nakano, R., "Probabilistic Mixture Subspace Method,"
Transactions of IEICE, Transactions of IEICEJ, Vol. J82DII, No. 12,
pp. 23942401, 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. J82DII, No. 5, pp. 930940, 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. 522530, 1999, (in
Japanese).
 Ueda, N. and Nakano, R., "Deterministic Annealing EM Algorithm,"
Neural Networks, Vol. 11, No. 2, pp. 271282, (1998).
 Ueda, N. and Nakano, R., "Analysis of Generalization Error on
Ensemble Learning," Transactions of IEICEJ, Vol. J80DII, No. 9, pp.
25122521, 1997, (in Japanese).
 Ueda, N. and Nakano, R., "Deterministic Annealing EM Algorithm,"
Transactions of IEICEJ, Vol. J80DII, No. 1, pp. 267276, 1997, (in
Japanese).
 Ueda, N. and Mase, K., "Tracking Moving Contours Using
Energyminimizing Elastic Contour Models," International Journal of
Pattern Recognition and Artificial Intelligence, Vol. 9, No. 3, pp.
465484, 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. 12111227, 1994.
 Ueda, N. and Nakano, R., "Competitive and Selective Learning
method for Vector Quantizer Design  Equidistortion Principle and Its
Algorithm ," Transactions of IEICEJ, Vol. J77DII, No. 11, pp.
22652278, 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. 337352, 1993, [ IEEE Transactions on Pattern Analysis and Machine
Intelligence (PAMI).
 Suzuki, S., Ueda, N. and Sklansky, J., "GraphBased Thinning for
Binary Images," International Journal of Pattern Recognition and
Artificial Intelligence, Vol. 7, No. 5 pp. 10091030, 1993.
 Ueda, N., Mase K., and Suenaga Y., "A Contour Tracking Method
Using Elastic Contour Model and Energy Minimization Approach,"
Transactions of IEICEJ, Vol. J75DII, No. 1, pp. 111120, 1992, (in
Japanese).
 Ueda, N. and Suzuki, S., "Automatic Shape Model Acquisition Based
on A Generalization of Convex/Concave Structure," Transactions of
IEICEJ, Vol. J74DII, No. 2, pp. 220229, 1991, (in Japanese).
 Ueda, N. and Suzuki, S., "A Deformed LineDrawing Matching
Algorithm Using Multiscale Convex/Concave Structures," Transactions of
IEICEJ, Vol. J73DII, No. 7, pp. 9921000, 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. 831836, 1988, (in
Japanese).
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 arXiv:1802.03039
[pdf, other]
stat.ML
Fewshot learning of neural networks from scratch by pseudo example optimization
Authors: Akisato Kimura, Zoubin Ghahramani, Koh Takeuchi, Tomoharu Iwata, Naonori Ueda
 arXiv:1711.11526
[pdf, other]
astroph.IM
doi
10.1109/ICDCSW.2017.47
Singleepoch supernova classification with deep convolutional neural networks
Authors: Akisato Kimura, Ichiro Takahashi, Masaomi Tanaka, Naoki Yasuda, Naonori Ueda, Naoki Yoshida
 arXiv:1705.07603
[pdf, other]
stat.ML
Multioutput Polynomial Networks and Factorization Machines
Authors: Mathieu Blondel, Vlad Niculae, Takuma Otsuka, Naonori Ueda
 arXiv:1609.03249
[pdf, ps, other]
astroph.IM
doi
10.1093/pasj/psw096
Machinelearning Selection of Optical Transients in Subaru/Hyper SuprimeCam Survey
Authors:
Mikio Morii, Shiro Ikeda, Nozomu Tominaga, Masaomi Tanaka, Tomoki
Morokuma, Katsuhiko Ishiguro, Junji Yamato, Naonori Ueda, Naotaka
Suzuki, Naoki Yasuda, Naoki Yoshida
 arXiv:1607.08810
[pdf, other]
stat.ML
Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms
Authors: Mathieu Blondel, Masakazu Ishihata, Akinori Fujino, Naonori Ueda
 arXiv:1607.07195
[pdf, other]
stat.ML
HigherOrder Factorization Machines
Authors: Mathieu Blondel, Akinori Fujino, Naonori Ueda, Masakazu Ishihata
 arXiv:1409.4757
[pdf, other]
cs.LG
Collapsed Variational Bayes Inference of Infinite Relational Model
Authors: Katsuhiko Ishiguro, Issei Sato, Naonori Ueda

Nakano, M., Kimura, A., Yamada, T, and
Ueda, N., "Baxter permutation process, "
Proc. of Neural Information Processing Systems,
NeurIPS 2020.
 Yamaguchi, Y., Saito, K., Hirahara, K., and Ueda, N.,
"Spatiotemporal clustering of earthquakes based on average
magnitudes," Proc. of International Conference on Complex Networks and
their Applications, 2020.
 Yamaguchi, T.,
Ichimura, T., Fujita, K., Hori, M., Wijerathne, L., and Ueda, N.,
"Datadriven approach to inversion analysis of threedimensional inner
soil structure via wave propagation analysis," Proc. of International
Conference on Computational Science (ICCS2020).
 Fujiwara、Y., Kumagai, A., Kanai, S., Ida, Y., and Ueda,
N.,"Efficient algorithm for the bmatching graph," proc. of ACM
SIGKDD 2020.

Miyoshi, T., Honda,T., Otsuka,S., Amemiya,
A., Maejima,Y., Ishikawa, Y., Seko, H.,Yoshizaki,Y., Ueda,N., Tomita, H.,
Ishikawa,Y., Satoh,S., Ushio,T., Koike,K., and Nakada, Y., "Big data
assimilation: Realtime workflow for 30secondupdate forecasting and
perspectives toward DAAI integration," Proc. of EGU General Assembly,
EGU20202483, 2020.
 Kalantar, B., Ueda, N., AlNajjar, H. A.
H.Saeidi, V., Gibril, M. B. A, Halin, A.,"A comparison between three
conditioning factors dataset for landslide prediction in the Sajadrood
Catchment of Iran," Proc. of ISPRS Annals of the Photogrammetry, Remote
Sensing and Spatial Information Sciences (ISPRS), 2020.
 Yamaguchi, T., Ichimura, T., Fujita, K., Naruse,A., Wells,J.C., Zimmer,
C. J., Straatsma,T.P., Hori,M., Lalith, W., and Ueda, N., "Implicit
loworder finite element solver with small matrixmatrix multiplication
accelerated by AIspecific hardware," Proc. Of Platform for Advanced Scientific Computing Conference (PASC2020), 2020.
 Ichimura, T., Fujita, K., Yamaguchi, T.,
Hori, M., Wijerathne, L., and Ueda, N, “Fast multistep optimization with deep
learning for datacentric supercomputing,” The 4th International Conference on High
Performance Compilation, Computing and Communications, 2020.
 Iwata, T., Fujino, A., Ueda, N., "Semisupervised Learning for
maximizing the partial AUC," Proc. of Association for the Advancement
of Artificial Intelligence (AAAI2020), 2020.

Okawa, M., Iwata, T., Kurashima, T.,
Tanaka, Y., Yoda, H., and Ueda, N., "Deep mixture point processes:
Spatiotemporal event prediction with rich contextual information," Proc.
of ACM SIGKDD2019, 2019.
 Hachiya, H., Hirahara,K.,and Ueda,
N.,"Machine learning approach for adaptive integration of multiple
relative intensity models toward improved earthquake forecasts in Japan,"
International Union of Geodesy and Geophysics (IUGG2019), 2019.
 Hachiya, H., Yamamoto, Y., Hirahara, K,
and Ueda, N., "Adaptive truncated residual regression for finegrained
regression problems," Proc. of Asian Conference on Machine Learning
(ACML), 2019.
 Miyoshi, T., Otsuka, S., Honda, T., Lien,
G., Maejima, Y., Ohhigashi, M., Yoshizaki, Y.,
Seko, H., Tomita, H., Satoh, S., Ushio, T., Gerofi, B., Ishikawa, Y.,
Ueda, N., Koike, K., Nakada, Y., “Big data
assimilation: Past 6 years and future plans,” AMS 39th Conference on
Radar Meteorology, 2019.
*AMS: American Meteorological Society
 Otsuka,T.,Shimizu,H.,Iwata,T.,Naya,F.,Sawada,H., and
Ueda,N., "Bayesian optimization for crowd traffic control using
multiagent simulation," Proc. Intelligent transportation systems conference (ITSC), 2019.
 Omi, T, Ueda, N, and Aihara, K,"Fully neural based model for
general temporal point processes," Proc. Neural Information Processing
Systems, NeuriPS 2019.
 Okazaki, T, Hachiya, H, Ueda, N., Iwaki, A., Maeda, T. and
Fujiwara, H.,"Synthesis of broadband ground motions using embedding and
neural networks," Geophysical Research Abstracts, Vol. 21,
EGU20194590, EGU General Assembly 2019.
 Ichimura,T., Fujita, K.,Yamaguchi, T., Naruse,A., Wells, J.C.,
Zimmer, C. J.,Straatsma,T.,Hori, T., Puel,S., Becker, T.W., Hori,M.,
and Ueda, T,"2416PFLOPS fast scalable implicit solver on
lowordered unstructured finite elements accelerated by 1.10ExaFLOPS
kernel with reformulated AIlike algorithm: For equationbased
earthquake modeling," Proc. of International Conference for High
Performance Computing, Networking, Storage, and Analysis (SC2019). 2019.
 Kalantar, B., Ueda, N., AlNajjar, H.A.H., Gibril M. B. A., Lay,
U.S., Motevalli, A.,"An evaluation of landslide susceptibility mapping
using remote sensing data and machine learning algorithms in Iran.
ISPRS Annals of the Photogrammetry", Remote Sensing and Spatial
Information Sciences, 2019.
 Kalantar, B., Ueda, N., AlNajjar, H.A.H., Moayedi. H., Halin,
A.A., Mansor, S.,"UAV and LiDAR image registration: A surfbased
approach for ground control points selection", International Archives
of the Photogrammetry, Remote Sensing and Spatial Information Sciences
 ISPRS Archives, 2019.
 Kalantar, B., Ueda, N., Lay, U.S., AlNajjar, A.H.A., Halin,
A.A., "Conditioning factors determination for landslide susceptibility
mapping using support vector machine learning",IEEE International
Geoscience and Remote Sensing Symposium, 2019.
 Fujiwara,Y., Ida, Y., Kanai,S., Kumagai,A., Arai, J., and Ueda,
N., "Fast random forest algorithm via incremental upper bound," Proc.
of the 28th ACM International Conference on Information and Knowledge
Management (CIKM2019) , 2019.
 Okita, T., Hachiya,H.,Inoue, S.,and Ueda, N.,"Translation between
waves, wave2wave," Proc. of the 22nd International Conference on
Discovery Science (DS2019) , 2019.
 Fujiwara, Y., Kanai, S., Arai, J., Ida, Y., and Ueda, N.,
"Efficient data point pruning for oneclass SVM," Proc. of Association
for the Advancement of Artificial Intelligence (AAAI2019), 2019.
 Shimizu, H., Matsubayashi, T., Tanaka, Y., Iwata1, T., Ueda, N., and
Sawada, H.,"Improving route traffic estimation by considering staying
population," The 21st International Conference on Principles and
Practice of MultiAgent Systems (PRIMA), 2018.
 Kalantar, B., Mansor, S., Halin, A. A., Ueda, N., Shafri, H. Z. M. and
Zand, M., "A graphbased approach for moving objects detection from UAV
videos," Proc. of SPIE Image and Signal Processing for Remote Sensing,
Vol.10789, 2018.
 Kalantar, B., Ueda, N., ALNajjar, H. A. H., Idrees, M. O., Motevalli,
A. and Pradhan, B., "Landslide susceptibility mapping at dodangeh
watershed, Iran, using LR and ANN models in GIS," Proc. of SPIE Earth
Resources and Environmental Remote Sensing, Vlo.10790, 2018.
 zeez, O. S., Kalantar, B., AlNajjar, H. A. H., Halin, A. A., Ueda, N.
and Mansor, S., "Object boundaries regularization using the dynamic
polyline compression algorithm," The International Archives of the
Photogrammetry, Remote Sensing and Spatial Information Science
(ISPRS2018), Vol.XLII4, pp. 541546, 2018.
 Yonezawa, T., Takeuchi, K., Itoh, T., Sakamura, N., Kishino, Y.,
Naya, F, Ueda, N. and Nakazawa, J., "Accelerating urban science by
crowdsensing with civil officers," Proc. of ACM International Joint
Conference on Pervasive and Ubiquitous Computing (UbiComp2018), 2018.
 Kishino, Y., Shirai, Y., Takeuchi, K., Suyama, T., Naya, F. and
Ueda, N., "Regional Garbage Amount Estimation and Analysis using
CarMounted Motion Sensor," Proc. of ACM International Joint Conference
on Pervasive and Ubiquitous Computing (UbiComp2018), 2018.
 Fujiwara, Y., Arai, J., Kanai, S., Ida, Y. and Ueda, N.,
"Adaptive data pruning for support vector machines," Proc. of IEEE
International Conference on Big Data, 2018.
 Choffin, B., and Ueda, N.,"Scaling Bayesian optimization up to higher
dimensions: A review and comparison of recent algorithms," Proc. of IEEE
International Workshop on Machine Learning for Signal Processing
(MLSP2018), 2018.
 Kimura, A., Gharamani, Z., Takeuchi, K., Iwata, T., and Ueda, N.,
"Fewshot learning of neural networks from scratch by pseudo example
optimization, " Proc. of 29th British Machine Vison Confernece（BMVC), 2018.
 Tanaka, Y., Iwata, T, Kurashima, T., Toda, H., and Ueda, N., "Estimating
latent people flow without tracking individuals," International
Conference on Artificial Intelligence (IJCAI), July 2018.
 Kimura, A., Takahashi, I., Tanaka, M., Yasuda, N., Ueda, N., and
Yoshida, N., "Singleepoch supernova classification with deep
convolutional neural networks," Proc. USJapan Workshop on Collaborative
Global Research on Applying Information Technology, in conjunction with
ICDCS 2017.
 Blondel, M., Niculae, V., Otsuka, T., and Ueda, N., "Multioutput
polynomial networks and factorization machine, "Proc. Neural
Information Processing Systems (NIPS2017), 2017.
 Kishino, Y., Takeuchi, K., Shirai, Y., Naya, F., and Ueda, N.,
"Datafying city: detecting and accumulating sptiotemporal events by
vehiclemounted sensors, "Proc of International Workshop on Smart
Cities (IWSC2017), 2017.
 Takeuchi, K., Kashima, H., and Ueda, N., "Autoregressive tensor
factorization for spatiotemporal predicitons," Proc. of IEEE
Ineternationl Conference on Data Mining (ICDM2017), 2017.
 Fujiwara, Y., Marumo, N., Blondel, M., Takeuchi, K., Kim, H., Iwata, T. and Ueda, N., "Scaling Locally Linear Embedding,"
In Proc. SIGMOD 2017, pp. 14791492, 2017.
 Kim, H., Iwata, T., Fujiwara, Y. and Ueda, N., "Read the Silence:
WellTimed Recommendation via Admixture Marked Point Processes," In
Proc. AAAI 2017, pp. 132139, 2017.
 Ichimura1, T., Fujita1, K., Yamaguchi, T., Hori1, M., Lalith1, M. and
Ueda, N., "AI with Supercomputed Data for Monte Carlo Earthquake
Hazard Classification," Proc. of the international conference for high
performance computing, networking, storage and analysis (SC2017), 2017.
 Kimura, A., Takahashi, I., Tanaka, M., Yasuda, N., Ueda, N. and Yoshida,
N., "Singleepoch supernova classification with deep convolutional
neural
networks," The 1st USJapan Workshop 2017, 2017.
 Toda, T., Inoue, S. and Ueda, N., "Mobile activity recognition
through training labelswith inaccurate activity segments," 13th
Annucal International Conference on Mobile and Ubiquitous Systems 2016
(MobiQuious2016), 2016.
 Blondel, M., Ishihata, M., Fujino, A. and Ueda, N., "Higherorder factorization machines," Advances in Neural Information Processing Systems (NIPS2016), 2016.
 Fujino, A. and Ueda, N., "A semisupervised AUC optimization
method with generative models," IEEE International Conference on Data
Mining (ICDM2016), 2016.
 Takeuchi, K. and Ueda, N., "Graph regularized nonnegative
tensor completion for spatiotemporal data analysis," The Second
International Workshop on Smart Cities, 2016.
 M.
Blondel, Fujino, A. and Ueda, N., "Polynomial Networks and
Factorization Machines: New Insights and Efficient Training
Algorithms," International Conference on Machine
Learning (ICML2016), 2016.
 Ishiguro, K., Sato, I., Ueda, N., Nakano, M. and Kimura, S.,
"Infinite plaid models for infinite biclustering," Proc. the 27th AAAI
Conference on Artificial Intelligence (AAAI2016), 2016.
 Ueda, N., Naya, F., Shimizu, H., Iwata, T., Okawa, M. and Sawada, H., "Realtime and proactive navigation via spatiotemporal prediction,
"Proceedings of the 2015 ACM International Joint Conference on
Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM
International Symposium on Wearable Computers(UbiComp 2015),
pp. 15591566, 2015.
 Inoue, S., Ueda., N., Nohara, Y. and Nakashima, N., "Mobile activity recognition for a whole day: recognizing real nursing activities with big dataset,"
Proceedings of the 2015 ACM International Joint Conference on Pervasive
and Ubiquitous Computing(UbiComp2015), pp. 12691280, 2015.
 Baba, Y., Kashima, H., Nohara, Y., Kai, E., Ghosh, P., Islam, R.,
Ahmed, A., Kuroda, M., Inoue, S., Hiramatsu, T., Kimura, M., Shimizu,
S., Kobayashi, K., Tsuda, K., Sugiyama, M., Blondel, M., Ueda, N.,
Kitsuregawa, M. and Nakashima, N., "Predictive Approaches for LowCost Preventive Medicine Program in Developing Countries,"
Proceedings of the 21th ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining (KDD2015), pp. 16811690, 2015.
 Blondel, M., Fujino, A. and Ueda, N., "Convex Factorization Machines,"
Proceedings of European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases(ECML PKDD), Part II,
LNAI 9285, pp. 1935, 2015.
 Matsubara, Y., Sakurai, Y., Ueda, N. and Yoshikawa M., "Fast and
Exact
Monitoring of CoEvolving Data Streams," 2014 IEEE International Conference on Data Mining(ICDM), pp. 390399, 2014.
 Blondel, M., Fujino, A. and Ueda, N., "LargeScale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex," 22nd International Conference on Pattern Recognition
(ICPR2014),
pp. 12891294, 2014.
 Nakano, M., Ishiguro, K., Kimura, A., Yamada, T. and Ueda, N.,
"Rectangular tiling process," Proceedings of The 31st International Conference on Machine Learnin (ICML2014), pp. 361–369, 2014.
 Blondel, M., Kubota, Y. and Ueda, N., "Online PassiveAggressive
Algorithms for NonNegative Matrix Factorization and Completion,"
Proc. 17th International Conference on Artificial Intelligence and
Statistics
(AISTATS2014), Vol.33, pp. 96104, 2014.
 Ueda, N., Tanaka, Y. and Fujino, A., "Robust Naive Bayes Combination
of Multiple Classifications," The Impact of Applications on
Mathematics, Proceedings of the Forum of Mathematics for Industry 2013,
Springer, pp. 141156, 2014.
 Iwata, T., Hirao, T. and Ueda, N., "Unsupervised Cluster
Matching via Probabilistic Latent Variable Models," Proc. of the
24th AAAI Conference on Artificial Intelligence (AAAI2013), pp. 445451,
2013.
 Ishiguro,
K., Ueda, N. and Sawada, H., "Subset Infinite
Relational Models," Proc. International Conference on Artificial
Intelligence and Statistics (AISTATS 2012), Society for AI and
Statistics, Vo.
22, pp. 547555, 2012.
 Sawada, H., Kameoka, H., Araki, S. and Ueda, N., "Efficient
Algorithms for Multichannel Extensions of ItakuraSaito Nonnegative
Matrix Factorization," IEEE International Conference on Acoustics,
Speech, and Signal Processing (ICASSP 2012), pp. 261264, 2012.
 Sun, X., Kashima, H., Tomioka, R. and Ueda, N., "Large Scale
Reallife Action Recognition Using Conditional Random Fields with
Stochastic Training," 15th PacificAsia Conference on Knowledge
Discovery
and Data Mining (PAKDD 2011), Part II, LNAI 6635, pp. 222–233, 2011.
 Sun,
X., Kashima, H., Tomioka, R., Ueda, N. and Li, P., "A New MultiTask
Learning Method for Personalized Activity Recognition,"
11th IEEE International Conference on Data Mining (ICDM 2011), pp. 12181223, 2011.
 Sawada, H., Kameoka, H., Araki, S. and Ueda, N., "New
Formulations and Efficient Algorithms for Multichannel NMF," 2011 IEEE
Workshop on Applications of Signal Processing to Audio and Acoustics
(WASPAA2011), pp. 153156, 2011.
 Aoyama, K., Sawada, H., Ueda, N. and Saito, K., "Fast approximate
similarity seach based in degreereduced neighborhood graphs,"
Proceedings of the 17th ACM SIGKDD international conference on
Knowledge discovery and data mining (KDD 2011), pp. 10551063,
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. 229232, May, 2011.
 Iwata, T., Yamada, T., Sakurai, Y. and Ueda, N., "Online
Multiscale Dynamic Topic Models," Proc. the 16th ACM SIGKDD
international conference on Knowledge discovery and data mining (KDD
2010), pp. 663672, 2010.
 Sun, X., Kashima, H., Matsuzaki, T. and Ueda, N., "A Robust,
Accurate, and Fast Stochastic Gradient Training Method for Modeling
LatentInformation in Data," IEEE International Conference on Data
Mining (ICDM2010), pp.10671072, Sydney, Australia, 2010.
 Hachiya, H., Sugiyama, M. and Ueda, N., "Coping with new user problems: Transfer learning in
accelerometerbased human activity recognition," NIPS 2010
Workshop on Transfer Learning by Learning Rich Generative Models, 2010.
 Fujino, A., Ueda, N. and Nagata, M., "A Robust Semisupervised
Classification Method for Transfer Learning," Proc. of the 19th ACM
international conference on Information and knowledge management
(CIKM 2010), pp. 379388, 2010.
 Ishiguro, K., Iwata, T., Ueda, N. and Tenenbaum, J. B., "Dynamic Infinite Relational Model for Timevarying
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. 53585361,
2010.
 Usui, S., Kamiji, N. L., Taniguchi, T. and Ueda N., "RAST: A
Related Abstract Search Tool," International Conference on Neural
Information Processing (ICONIP2009), Part II, LNCS 5864, pp.
189–195, 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), pp. 835843, 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 (IJCAI09), pp. 14271432, 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.363371, 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. 18, 2008, [CVPR08]
 Usui, S., Naud, A., Ueda, N. and Taniguchi, T., "3DSE 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., "Oneshot Collaborative Filtering," IEEE CIDM2007,
Vol.1, No.1, pp.300307, 2007.
 Fujino, A., Ueda, N. and Saito, K., "Semisupervized
learning for
multicomponent data classification," Proc. of International Joint
Conference on Areificial Intelligence (IJCAI2007),
pp. 27542759, 2007.
 Kuwata, S. and Ueda N., "Oneshot collaborative filtering," Proc.
of IEEE Symposium on Compututational Intelligence and
Data Mining (CIDM2007), pp. 300307, 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(AAAI06), pp. 381388, 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.283288, 2006.
 Usui, S., Palmes P., Nagata, K., Taniguchi, T. and Ueda, N.,
"Extracting Keywords from Research Abstracts for the Neuroinformatics
Platform Index Tree," Proc. of International Joint
Conference on Neural Networks (IJCNN2006), pp.
50455050, 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), MoP08.3, pp.
364369, 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.6267, 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),
LNCS 3689, pp. 423–438, 2005.
 Kimura, M., Saito, K. and Ueda, N., "Multinomial PCA for
extracting major latent topics from document streams," Proc.
International Joint Conference on Neural Networks ( IJCNN2005), Vol. 1,
pp.238243,
2005.
 Fujino, A., Ueda, N. and Saito, K., "A hybrid
generative/discriminative approach to semisupervised classifier
design," Proc. of the 20th National Conference on Artificial
Intelligence (AAAI05), pp. 764769, 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
1417, pp.10311037, 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.
617624, 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 Multilabeled Text Categorization," Proc. of the 8th
International Conference on KnowledgeBased Intelligent Information
& Engineering Systems, Vol. 3214 of Lecture Notes in Computer
Science, pp. 616623, 2004.
 Ueda, N. and Saito, K., "Simplex mixture models for multitopic
text," In Science of Modeling, ISM Report on Research and Education
No.17, The Institute of Statisitical Mathematics, pp. 380381, 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.366367, 2003.
 Yamada, T., Saito, K. and Ueda, N., "Crossentropy based
embedding for relational data," International Conference on Machine
Learning (ICML2003), pp. 832839, 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. 4750, 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. 568571, 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. 1520, 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. 189198, 2002.
 Watanabe,
S., Minami, Y., Nakamura, A. and Ueda, N., "Application of Variational
Bayesian Approach to Speech Recognition," Proc. of Advances in Neural
Information Processing Systems 15 (NIPS15),
MIT Press, pp. 12611268, 2002.
 Watanabe, S., Minami, Y., Nakamura, A. and Ueda, N.,
"Constructing sharedstate HMMs based on a Bayesian approach,"
International Conference on Spoken Language Processing (ICSLP02), Vol.
4, pp. 26692672, 2002.
 Ueda, N. and Saito, K., "Parametric mixture models for
multitopic text," Neural Information Processing Systems 15 (NIPS15),
MIT Press, pp. 737744, 2002.
 Ueda, N. and Saito, K., "Singleshot detection of multicategory
text using parametric mixture models," ACM SIG Knowledge Discovery and
Data Mining (SIGKDD2002), pp. 626631, 2002.
 Inoue, M. and Ueda, N., "HMMs for both labeled and unlabed time
series data," IEEE Neural Networks for Signal Processing (NNSP2001),
pp. 93102, 2001.
 Ueda, N. and Ghahramani, Z., "Optimal model inference for Baysian
mixture of experts," IEEE Neural Networks for Signal Processing
(NNSP2000), pp. 145154, 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. 525534, 1999.
 Ueda, N., Nakano, R., Ghahramani, Z. and Hinton, G. E., "SMEM algorithm for mixture models," Neural
Information Processing Systems 11 (NIPS11), pp. 599605, 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.
274283, 1998.
 Ueda, N. and Nakano, R., "Combining discriminantbased
classifiers using the minimum classification error discrimininant,"
IEEE
Neural Networks for Signal Processing (NNSP97), pp. 365374, 1997.
 Suzuki, S. and Ueda, N., "Selforganization of feature columns
and its application to object classification," Proceedings of
International Conference on Neural Information Processing (ICONIP97),
pp. 11661169, 1997.
 Ueda, N. and Nakano, R, "Generalization error of ensemble
estimators," Proceedings of International Conference on Neural Networks
(ICNN96), pp. 9095, 1996.
 Ueda, N. and Nakano, R, "Deterministic annealing variant of the EM algorithm,"
Neural Information Processing Systems 7 (NIPS7), MIT Press, Cambridge
MA, pp. 545552, 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.
497504, 1995.
 Ueda, N. and Nakano, R, "Estimating expected error rates of
neural network classifiers in small sample size situations: A
comparison of crossvalidation and bootstrap," International Conference
on Neural Networks (ICNN95), pp. 101104, 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. 6977, 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.
362371, 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. 14441450,
1993.
 Ueda, N. and Mase, K., "Tracking moving contours using
energyminimizing elastic contour models," Proceedings of European
Conference on Computer Vision (ECCV92), pp. 453457, 1992.
 Suzuki, S. and Ueda, N., "Robust vectorization using graphbased
thnning and reliabilitybased line approximation," Proceedings of IEEE
Conference on Computer Vision (CVPR91), pp. 494500, 1991.
 Ueda, N. and Suzuki, S., "Automatic shape model acquisition using
multiscale segment matching," Proceedings of International Conference
on Pattern Recognition (ICPR90), pp. 897902, 1990.
 Ogawa, H. Kawada, E. and Ueda, N., "Application of image
processing equipment with multiprocessors to linedrawing recognition,"
Proceedings of SPIE845, pp. 97103, 1987.
 Okudaira, M. Ueda, N. and Aoki, U., "Image enhancement of
handwritten drawings and their recognition followed by interactive
processing," Proceedings of SPIE707, pp. 4250, 1986.
 Ueda, N, Tanaka, Y. and Fujino, A., "Bayesian MetaLearning and
its Application to HighLevel Real Nursing Activity Recognition Using
Accelerometers," Springer, 2014.
 Ueda, N., "Relational data analysis based on Bayesian models,"
IEICEJ, Vol.97, No.5, 2014 (in Japanese).
 Ueda, N., "Cyber Physical Systems, Creating New Value from Sensor
Network Information," NII Today, No.45, 2013.
 Fujino, A., Ueda, N. and Nagata, M., "Adaptive semisupervised
learning
on labeled and unlabeled data with different distributions," Knowledge
and Information Systems(KAIS), Vol. 37, Issue 1, pp. 129154, Springer,
2013, (invited paper).
 Ueda, N., "EM algorithm, "Society of Instrument and Control
Engineers(SICE)," Vol.44, No.5, pp.333338, 2005. (In Japanese)
 Ueda, N., "The goal of Web science research," OHM, Vol.91,
No.10,pp.67, 2004.(In Japanese)
 Ueda, N., "Bayesian Inference Algorithms Approximation Methods
for HighDimensional Integrals," Journal of the Japanese Society for
Artificial Intelligence, Vol. 19, No. 6, 2004 (in Japanese).
 Ueda, N. and Saito, K., "Probablistic Models for Multitopic
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. 730733,
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. 444449, 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. 689697, 1997 (in Japanse).
 Ueda, N. and 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. 3449, 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.
5970, 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. 89100, 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. 94104,
1991.
 Mase, S. and Ueda, N., "Mathematical Morphology and Image
Analysis I," Journal of IEICEJ, Vol. 64, No. 2, pp. 166174 , 1991 (in
Japanese).
 Ueda, N. and Mase, S., "Mathematical Morphology and Image
Analysis II," Journal of IEICEJ, Vol. 64, No. 3, pp. 271279, 1991 (in
Japanse).
 Ueda, N. ., "Challengers," NTT Technical Journal, Vol.29, No9, pp.3843, 2017 (In Japanese).
 Ueda, N. ., "Challengers," NTT Technical Journal, Vol.25,
No.9, pp.4043, 2013 (In Japanese).
 Ueda, N. ., "Machine learning technology making use of big data," NTT Technical Journal, Vol.25,
No.4, pp.3135, 2013 (In Japanese).
 Ueda, N., "Communication Science for the Big Data Era," NTT
Technical Review, Vol. 10, No. 11, 2012.
 Fujino, A., Ueda, N. and Saito, K., "Semisupervised learning
forautomatic text classification, " NTT Technical Journal, Vol.19,
No.6, pp.2628, 2007 (In Japanese).
 Ueda, N., "Web Science Research," NTT Technical Review, Vol. 3,
No. 3, pp. 1214, 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. 11751184, 1993 (in Japanese).
 Ueda, N., Mase, K., and Suenaga, Y., "Contour Tracking Method
Using Energyminimizing Elastic Models," NTT R&D, Vol. 42, No. 4,
pp. 477486, 1993 (in Japanese).
 Ueda, N. and Suzuki, S., "Multiscale Convex/Concave Structure
Matching : MC Matching Method," NTT R&D, Vol. 40, No. 3,
pp.399406, 1991 (in Japanese).
 Kawada, E., Ueda, N., Ogawa, H. and Kosugi, M., "A Figure
Recognition Method for HandWritten Drawings," NTT Electrical
Communications Laboratories Technical Journal, Vol. 37, No. 3, pp.
217223, 1988 (in Japanese).
 Ueda, N., Nagura, M., Hoshino, T. and Mori, K., "Image
Enhancement Method for HandWritten Line Drawings," NTT Electrical
Communications Laboratories Technical Journal, Vol. 37, No. 3, pp.
211216, 1988 (in Japanese).
 Ueda, N., "Datadriven Science," KADOKAWA CourseInternet
(Masao Sakauchi, editorinchief), Vol. 7, Part 1, Chap. 5, 2015.(in
Japanese)
 Ishii, K. and Ueda, N., "Introduction to Pattern Recognition,
Part IIUnsupervised Learning" OhmSha, Tokyo, Japan, 2014.(in
Japanese)
 Ueda, N., Japanese translation: "Statistics," Science Palette, Maruzen Publishing, 2014.(in Japanese)
(Original: David J. Handm, "Statistics: VSI," Oxford Univ. Press.)
 Ueda. N., "Variational Bayes method" Science dictionary (2nd ed.), Heisuke Hironaka edu., 2009.(in Japanese)
 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," OhmSha, Tokyo, Japan, 1998.(in Japanese)
 Ueda, N., "Chapter 3: Pattern Recognition Theory," in IEICEJ
(Ed.),"Handbook of Electronics, Information and Communication,"
AsakuraShoten, Tokyo, Japan, 1998.(in Japanese)
 Ueda, N., "Chapter 9: Vector Quantization," in Amari, S.
(Ed.),"Handbook of Brain Science," AsakuraShoten, Tokyo, Japan,
1995.(in Japanese)
 NTT Human Interface Laboratory, Project RTV, Japanese translation
of "Horn, B. K. P., Robot Vision, MITPress, 1986" AsakuraShoten,
Tokyo, Japan, 1993. (in Japanese)
Naonori UEDA