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Research scientist [CV] Photo
Lab. For Advanced Brain Signal Processing, Brain Science Institute, RIKEN
2-1, Hirosawa, Wakoshi, Saitama 351-0198, Japan
Tel: +81-48-462-1111 (Ex. 7171)
Email: guoxu.zhou(at)riken.jp

Research Interests
  • Big data analytics

  • Statistical signal processing, blind source separation

  • Penalized matrix and tensor decomposition

  • Machine learning algorithms and applications

 

Software


Selected Publications
  1. Guoxu Zhou, Qibin Zhao, Yu Zhang, Tulay Adalı, Shengli Xie, and Andrzej Cichocki, "Linked Component Analysis from Matrices to High Order Tensors: Applications to Biomedical Data", Proceedings of the IEEE. Accepted. DOI: http://10.1109/JPROC.2015.2474704. 2015.

  2. Guoxu Zhou, Andrzej Cichocki, Yu Zhang, and Danilo Mandic. "Group Component Analysis from Multi-block Data: Common and Individual Feature Extraction,” IEEE Transactions on Neural Networks and Learning Systems, Accepted. DOI: 10.1109/TNNLS.2015.2487364. 2015.

  3. Guoxu Zhou, Andrzej Cichocki, Qibin Zhao, and Shengli Xie, "Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness," IEEE Transactions on Image Processing, vol.24, no.12, pp.4990-5003, Dec. 2015.

  4. Yu Zhang, Guoxu Zhou*, Qibin Zhao, Fuxing Wang, Andrzej Cichocki, “Fast Nonnegative Tensor Factorization Based on Accelerated Proximal Gradient and Low-rank Approximation”, Neurocomputing. Accepted.

  5. Yu Zhang, Guoxu Zhou, Jing Jin, Qibin Zhao, Xinyu Wang, and Andrzej Cichocki, "Sparse Bayesian Classification of EEG for Brain-Computer Interface," IEEE Transactions on Neural Networks and Learning Systems, vol.PP, no.99, pp.1-1, 2015.

  6. Qibin Zhao, Guoxu Zhou, Liqing Zhang, Andrzej Cichocki, and S.-I. Amari, "Bayesian Robust Tensor Factorization for Incomplete Multiway Data," IEEE Transactions on Neural Networks and Learning Systems, vol.PP, no.99, pp.1-1, 2015.

  7. Yu Zhang, Guoxu Zhou, Jing Jin, Xingyu Wang, Andrzej Cichocki, "Optimizing spatial patterns with sparse filter bands for motor-imagery based brain–computer interface," Journal of Neuroscience Methods, vol. 255, no. 30, Pages 85-91, Nov. 2015.

  8. Yu Zhang, Guoxu Zhou, Jing Jin, Xingyu Wang, and Andrzej Cichocki, "SSVEP recognition using common feature analysis in brain–computer interface," Journal of Neuroscience Methods, Vol. 244, no. 15, Pages 8-15, Apr. 2015.

  9. Bo Li, G. Zhou*, A. Cichocki, "Two Efficient Algorithms for Approximately Orthogonal Nonnegative Matrix Factorization," IEEE Signal Processing Letters, vol.22, no.7, pp.843,846, July 2015. [URL][Matlab code]

  10. Fengyu Cong#, Guoxu Zhou#, Piia Astikainen, Qibin Zhao, Qiang Wu, Asoke K Nandi, Jari K Hietanen, Tapani Ristaniemi, Andrzej Cichocki, "Low-Rank Approximation Based Non-Negative Multi-Way Array Decomposition On Event-Related Potentials," International Journal of Neural Systems, vol. 24, no. 8, 2014.

  11. G. Zhou, A. Cichocki, Q. Zhao, and S. Xie, Nonnegative Matrix and Tensor Factorizations: An algorithmic perspective, IEEE Signal Processing Magazine, vol.31, no.3, pp.54--65, May 2014 [Link] [Matlab code]

  12. A Cichocki, C Mandic, AH Phan, C Caiafa, G Zhou, Q Zhao, and L De Lathauwer, Tensor Decompositions for Signal Processing Applications. From two-way to multiway component analysis. IEEE Signal Processing Magazine, (accepted), 2014.

  13. G. Zhou, A. Cichocki, and S. Xie, Accelerated canonical polyadic decomposition by using mode reduction, IEEE Transactions on Neural Networks and Learning Systems, vol.24, no.12, pp.2051--2062, Dec. 2013, http://arxiv.org/abs/1211.3500. [Link]

  14. Q. Zhao, G. Zhou, T. Adali, L. Zhang and A. Cichocki. Kernelization of Tensor-based Models for Multimodal Data Analysis. IEEE Signal Processing Magazine, vol.30, no.4, pp.137--148, July 2013. [Link].

  15. Y. Zhang, G. Zhou, J. Jin, M. Wang, X. Wang, and A. Cichocki, L1-regularized multiway canonical correlation analysis for SSVEP-based BCI, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.21, no.6, pp. 887--896, 2013.

  16. Y. Zhang, G. Zhou, J. Jin, X. Wang, and A. Cichocki, Frequency recognition in SSVEP-based BCI using multiset canonical correlation analysis,'' International Journal of Neural Systems, Vol.24, No.4 (2014) 1450013 (14 pages) [Link]

  17. Y. Zhang, G. Zhou, J. Jin, Q. Zhao, X. Wang, and A. Cichocki, Aggregation of sparse linear discriminant analyses for event-related potential classification in brain-computer interface, International Journal of Neural Systems, vol.24, no.1 (2014), 1450003(15 pages). [Link]

  18. G. Zhou, A. Cichocki, and S. Xie, Fast nonnegative matrix/tensor factorization based on low-rank approximation, IEEE Transactions on Signal Processing, vol. 60, no. 6, pp. 2928--2940, June 2012. [PDF] [Link] [Matlab code] Last update: 09-13-2013.

  19. G. Zhou and A. Cichocki, Canonical polyadic decomposition based on a single mode blind source separation, IEEE Signal Processing Letters, vol. 19, no. 8, pp. 523--526, Aug. 2012. [PDF] [Link] [Matlab code: TDALAB]

  20. G. Zhou and A. Cichocki, Fast and unique Tucker decompositions via multiway blind source separation, Bulletin of the Polish Academy of Sciences-Technical Sciences, vol. 60, no. 3, p. 389405, 12 2012. [PDF] [Link] [Matlab code: TDALAB]

  21. G. Zhou, Z. Yang, S. Xie, and J.-M. Yang, Online blind source separation using incremental nonnegative matrix factorization with volume constraint, IEEE Transactions on Neural Networks, vol. 22, no. 4, pp. 550--560, April 2011. [Link]

  22. G. Zhou, S. Xie, Z. Yang, J.-M. Yang, and Z. He, Minimum-volume constrained nonnegative matrix factorization: Enhanced ability of learning parts, IEEE Transactions on Neural Networks, vol. 22, no. 10, pp. 1626--1637, Oct. 2011. [Link]

  23. G. Zhou, Z. Yang, S. Xie, and J.-M. Yang, Mixing matrix estimation from sparse mixtures with unknown number of sources, IEEE Transactions on Neural Networks, vol. 22, no. 2, pp. 211-221, Feb. 2011. [Link]

  24. G. Zhou, S. Xie, Z. Yang, and J. Zhang, Nonorthogonal approximate joint diagonalization with well-conditioned diagonalizers, IEEE Transactions on Neural Networks, vol. 20, no. 11, pp. 1810-1819, Nov 2009. [Link]

  25. Z. Yang, G. Zhou, S. Xie, S. Ding, J.-M. Yang, and J. Zhang, Blind spectral unmixing based on sparse nonnegative matrix factorization, IEEE Transactions on Image Processing, vol. 20, no. 4, pp. 1112-1125, 2011. [Link]

  26. Y. Zhang, G. Zhou, Q. Zhao, J, J, X. Wang, and A. Cichocki, Spatial-temporal discriminant analysis for ERP-based brain-computer interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol.21, no.2, 2013. [Link]

  27. S. Xie, L. Yang, J.-M. Yang, G. Zhou, and Y. Xiang, Time-frequency approach to underdetermined blind source separation, IEEE Transactions on Neural Networks and Learning Systems, vol. 23, no. 2, pp. 306--316, Feb.2012. [Link]

  28. Z. He, S. Xie, R. Zdunek, G. Zhou, and A. Cichocki, Symmetric nonnegative matrix factorization: Algorithms and applications to probabilistic clustering, IEEE Transactions on Neural Networks, vol. 22, no. 12, pp. 2117-2131, Dec. 2011. [Link]



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