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Publications

Journal papers (refereed)

• J. Hirayama, A. Hyvärinen, V. Kiviniemi, M. Kawanabe and O. Yamashita. Characterizing variability of modular brain connectivity with constrained principal component analysis. PLoS ONE, 11(12): e0168180, 2016. [paper] [Matlab code]
• J. Hirayama, A. Hyvärinen and S. Ishii. Sparse and low-rank matrix regularization for learning time-varying Markov networks. Machine Learning, 105(3), 335-366, 2016. [paper] [paper2]
• A. Hyvärinen, J. Hirayama, V. Kiviniemi and M. Kawanabe. Orthogonal connectivity factorization: Interpretable decomposition of variability in correlation matrices. Neural Computation, 28(3), 445-484, 2016. [Matlab code & preprint]
• J. Hirayama, T. Ogawa and A. Hyvärinen. Unifying blind separation and clustering for resting-state EEG/MEG functional connectivity analysis. Neural Computation, 27(7), 1373-1404, 2015. [paper] [Matlab code]
• H. Morioka, A. Kanemura, J. Hirayama, M. Shikauchi, T. Ogawa, S. Ikeda, M. Kawanabe and S. Ishii. Learning a common dictionary for subject-transfer decoding with resting calibration. NeuroImage, 111, 167-178, 2015. [Matlab code]
• J. Hirayama, M. Nakatomi, T. Takenouchi and S. Ishii. Collaborative prediction by multiple Bayesian networks and its application to printer usage modeling. Behaviormetrika, 35(2), 99-114, 2008. [paper]
• J. Hirayama, M. Nakatomi, T. Takenouchi and S. Ishii. α-Bayesian collaboration of multiple predictors and its applications to hybrid recommendation and user modeling. Neural Information Processing - Letters and Reviews, 12(1-3), 11-20, 2008. [paper]
• S. Osaga, J. Hirayama, T. Takenouchi and S. Ishii. A probabilistic modeling of MOSAIC learning. Artificial Life and Robotics, 12, 167-171, 2008. [doi]
• J. Hirayama, S. Maeda and S. Ishii. Markov and semi-Markov switching of source appearances for non-stationary independent component analysis. IEEE Transactions on Neural Networks, 18(5), 1326-1342, 2007. [doi]
• J. Hirayama, J. Yoshimoto and S. Ishii. Balancing plasticity and stability of on-line learning based on hierarchical Bayesian adaptation of forgetting factors. Neurocomputing, 69(16-18), 1954-1961, 2006. [doi]
• J. Hirayama, J. Yoshimoto and S. Ishii. Bayesian representation learning in the cortex regulated by acetylcholine. Neural Networks, 17(10), 1391-1400, 2004. [doi]

Conference proceedings (refereed)

• T. Miyanishi, J. Hirayama, T. Maekawa & M. Kawanabe. Generating an event timeline about daily activities from a semantic concept stream. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI'18), to appear.
• J. Hirayama, T. Ogawa T, H. Moriya A. Hyvärinen, M. Kawanabe. Exploring EEG source resting-state networks by SPLICE: A simultaneous fMRI study. Real-time Functional Imaging and Neurofeedback Conference (rtFIN2017), 2017.
• T. Ogawa, H. Moriya, T. Yamada, M. Kawanabe & J. Hirayama. Prediction of resting state fMRI signatures from EEG signal: a study of EEG-fMRI simultaneous recording. Real-time Functional Imaging and Neurofeedback Conference (rtFIN2017), 2017.
• H. Moriya, T. Ogawa, M. Kawanabe, J. Hirayama. Predictability of amygdala BOLD signal from multiple-electrode EEGs. Real-time Functional Imaging and Neurofeedback Conference (rtFIN2017), 2017.
• J. Hirayama, A. Hyvärinen and M. Kawanabe. SPLICE: fully tractable hierarchical extension of ICA with pooling. Proceedings of the 34th International Conference on Machine Learning (ICML'17), PMLR 70:1491-1500, 2017. [paper]
• T. Miyanishi, J. Hirayama, Q. Kong, T. Maekawa, H. Moriya and T. Suyama. Egocentric video search via physical interactions.The 30th AAAI Conference on Artificial Intelligence (AAAI'16), pp.330-336, 2016. [paper]
• T. Ogawa, J. Hirayama, P. Gupta, H. Moriya, S. Yamaguchi, A. Ishikawa, Y. Inoue, M. Kawanabe and S. Ishii. Brain-machine interfaces for assistive smart homes: A feasibility study with wearable near-infrared spectroscopy. The 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'15), pp.1107-1110, 2015.
• T. Ogawa, J. Hirayama, P. Gupta, J. Abdur-Rahim, H. Moirya, K. Yano, M. Kawanabe and S. Ishii. An application of NIRS-based brain machine interface in the realistic environment: supporting appliance control with online single-trial decoding. The 38th Annual Meeting of the Japan Neuroscience Society, 2015.
• J. Abdur-Rahim, T. Ogawa, J. Hirayama and S. Ishii. Database-driven artifact detection method for EEG systems with few channels (DAD). IEEE Biomedical Circuits and Systems Conference (BioCAS'14), pp.5-8, 2014.
• J. Hirayama, T. Ogawa and A. Hyvärinen. Simultaneous blind separation and clustering of coactivated EEG/MEG sources for analyzing spontaneous brain activity. The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'14), pp.4932-4935, 2014.
• A. Hyvärinen, J. Hirayama and M. Kawanabe. Dynamic Connectivity Factorization: Interpretable decompositions of non-stationarity. Proc. Workshop on Pattern Recognition in Neuroimaging (PRNI'14), 2014.
• J. Hirayama and A. Hyvärinen. Structural equations and divisive normalization for energy-dependent component analysis Advances in Neural Information Processing Systems 24 (NIPS'11), pp.1872-1880, 2011. [paper]
• M. U. Gutmann and J. Hirayama. Bregman divergence as general framework to estimate unnormalized statistical models. Proc. Conf. on Uncertainty in Artificial Intelligence (UAI'11), pp.283-290, 2011. [paper]
• J. Hirayama, A. Hyvärinen and S. Ishii. Sparse and low-rank estimation of time-varying Markov networks with alternating direction method of multipliers. International Conference on Neural Information Processing (ICONIP'10), 2010. Lecture Notes in Computer Science, 6443, pp.371-379, 2010. [doi]
• K. Hayashi, J. Hirayama and S. Ishii. Dynamic Exponential Family Matrix Factorization. The 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'09), 2009. Lecture Notes in Computer Science, 5476, pp.452-462, 2009. [doi]
• A. Asahina, J. Hirayama and S. Ishii. Interpreting dopamine activities in stochastic reward tasks. International Conference on Neural Information Processing (ICONIP'08), 2008. (Best APNNA student paper award) Lecture Notes in Computer Science, 5506, pp.361-368, 2009. [doi]
• J. Hirayama and S. Ishii. A closed-form estimator of fully visible Boltzmann machines. International Conference on Neural Information Processing (ICONIP'08), 2008. Lecture Notes in Computer Science, 5507, pp.951-959, 2009. [doi]
• A. Ishihara, J. Hirayama, T. Takenouchi and S. Ishii. A unified approach to collaborative and feature-based recommendation based on probabilistic latent semantic models. International Symposium on Artificial Life and Robotics (AROB'08), GS17-2, 2008.
• J. Hirayama, M. Nakatomi, T. Takenouchi and S. Ishii. Bayesian collaborative predictors for general user modeling tasks. International Conference on Neural Information Processing (ICONIP'07), 2007. Lecture Notes in Computer Science, 4984, pp.742-751, 2008. [doi]
• S. Osaga, J. Hirayama, T. Takenouchi and S. Ishii. A probabilistic model of MOSAIC. The First IEEE Symposium on Foundations of Computational Intelligence (FOCI'07), pp.41-46, 2007. [doi]
• S. Osaga, J. Hirayama, T. Takenouchi and S. Ishii. A probabilistic modeling of MOSAIC learning. Artificial Life and Robotics (AROB'07), GS16-3, 2007.
• J. Hirayama, S. Maeda and S. Ishii A Bayesian approach to blind source separation with variable number of sources. Artificial Life and Robotics (AROB'06), GS19-6, 2006. (Young author award)
• J. Hirayama, S. Maeda and S. Ishii. Bayesian noisy ICA for source switching environments. IEEE Workshop on Statistical Signal Processing (SSP'05), 232, 2005. [doi]
• J. Hirayama, J. Yoshimoto and S. Ishii. Cortical representation learning regulated by acetylcholine. Brain Inspired Cognitive Systems (BICS'04), ICESS.3, 2004. [paper]

Other publications and presentations

• A. Kanemura, J. Hirayama, T. Miyanishi, H. Moriya, T. Ogawa, H. Celikkanat, H. Morioka, A. Hyvärinen, and M. Kawanabe. Machine Learning for Multimodal Sensors: Towards Life-Logging Affective States of Humans. Healthy Aging Tech mashup service, data and people (HAT-MASH2016), 2016.
• Hyvärinen, A., Hirayama, J., Kiviniemi, V. and Kawanabe, M. Analyzing non-stationarity of connectivity by a new matrix decomposition method. Organization for Human Brain Mapping (OHBM2016), 2016.
• Morioka, H., Kanemura, A., Hirayama, J., Shikauchi, M., Ogawa, T., Ikeda, S., Kawanabe, M., and Ishii, S. Learning a common dictionary for subject-transfer decoding with resting calibration. Workshop on Improving BCI usability through transfer learning methods, International BCI Meeting, 30th May-3rd June, 2016.
• Hirayama, J., Ogawa, T. and Hyvärinen, A. Unifying blind separation and clustering for resting-state EEG/MEG functional connectivity analysis. Germany-Japan Adaptive BCI Workshop, 29th October, 2015.
• Hirayama, J., Ogawa, T. and Hyvärinen, A. Unifying blind separation and coactivation clustering for resting-state EEG/MEG analysis. CiNet Lunch Seminar. 11th September, 2015.
• Ogawa, T., Gupta, P. K., Yano, K., Abdur-Rahim, J., A., Morioka, H., Hirayama, J., Yamaguchi, S., Ishikawa, A., Inoue, Y., Kawanabe, M. and Ishii, S. Decoding daily behaviors from NIRS signatures by using a portable NIRS device in the daily-life environment. Society for Neuroscience. 2014.
• Morioka, H., Kanemura, A., Hirayama, J., Ogawa, T., Ikeda, S., Kawanabe, M. and Ishii, S. Subject-Independent Decoding from EEG through Sparse Learning of Spatial Bases Common Across Sessions and Subjects. INCF Japan Node International Workshop: Advances in Neuroinformatics. 2014
• A. K. Singh, T. Ogawa, J. Hirayama, M. Maruyama, M. Kawanabe and S. Ishii. Spatio-temporal and cortical characterization of EEG changes during motor imagery. Front. Neuroinform. Conference Abstract: Neuroinformatics 2013., 2013.

See here for other publications in Japanese