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2020 – today
- 2020
[j34]Xiaobo Gu
, Guoxu Zhou, Jianzhong Li, Shengli Xie:
Joint Time Synchronization and Ranging for a Mobile Wireless Network. IEEE Commun. Lett. 24(10): 2363-2366 (2020)- [j33]Yali Feng, Guoxu Zhou:
Orthogonal random projection for tensor completion. IET Comput. Vis. 14(5): 233-240 (2020) - [j32]Jianqiang Li, Guoxu Zhou, Yuning Qiu, Yanjiao Wang, Yu Zhang, Shengli Xie:
Deep graph regularized non-negative matrix factorization for multi-view clustering. Neurocomputing 390: 108-116 (2020) - [j31]Zhichao Jin, Guoxu Zhou, Daqi Gao, Yu Zhang:
EEG classification using sparse Bayesian extreme learning machine for brain-computer interface. Neural Comput. Appl. 32(11): 6601-6609 (2020) - [j30]Na Han, Jigang Wu, Xiaozhao Fang, Shaohua Teng, Guoxu Zhou, Shengli Xie, Xuelong Li:
Projective Double Reconstructions Based Dictionary Learning Algorithm for Cross-Domain Recognition. IEEE Trans. Image Process. 29: 9220-9233 (2020) - [j29]Kan Xie, Guoxu Zhou, Junjie Yang, Zhaoshui He, Shengli Xie:
Eliminating the Permutation Ambiguity of Convolutive Blind Source Separation by Using Coupled Frequency Bins. IEEE Trans. Neural Networks Learn. Syst. 31(2): 589-599 (2020) - [i13]Yuyuan Yu, Guoxu Zhou, Ning Zheng, Shengli Xie, Qibin Zhao:
Graph Regularized Nonnegative Tensor Ring Decomposition for Multiway Representation Learning. CoRR abs/2010.05657 (2020) - [i12]Yu Zhang, Tao Zhou, Wei Wu, Hua Xie, Hongru Zhu, Guoxu Zhou, Andrzej Cichocki:
Improving EEG Decoding via Clustering-based Multi-task Feature Learning. CoRR abs/2012.06813 (2020)
2010 – 2019
- 2019
- [j28]Yu Zhang, Chang S. Nam, Guoxu Zhou, Jing Jin, Xingyu Wang, Andrzej Cichocki:
Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCI. IEEE Trans. Cybern. 49(9): 3322-3332 (2019) - [c15]Yuning Qiu, Guoxu Zhou, Yu Zhang, Shengli Xie:
Graph Regularized Nonnegative Tucker Decomposition for Tensor Data Representation. ICASSP 2019: 8613-8617 - [i11]Jinshi Yu, Chao Li, Qibin Zhao, Guoxu Zhou:
Tensor-Ring Nuclear Norm Minimization and Application for Visual Data Completion. CoRR abs/1903.08888 (2019) - 2018
- [j27]Jinshi Yu, Guoxu Zhou, Andrzej Cichocki, Shengli Xie:
Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization. IEEE Access 6: 58096-58105 (2018) - [j26]Yu Zhang, Yu Wang, Guoxu Zhou, Jing Jin, Bei Wang, Xingyu Wang, Andrzej Cichocki:
Multi-kernel extreme learning machine for EEG classification in brain-computer interfaces. Expert Syst. Appl. 96: 302-310 (2018) - [c14]Jinshi Yu, Guoxu Zhou, Qibin Zhao, Kan Xie:
An Effective Tensor Completion Method Based on Multi-linear Tensor Ring Decomposition. APSIPA 2018: 1344-1349 - [c13]Yali Feng, Guoxu Zhou, Yuning Qiu, Weijun Sun:
Orthogonal Random Projection Based Tensor Completion for Image Recovery. APSIPA 2018: 1350-1354 - [c12]Jiancong He, Guoxu Zhou, Hongtao Wang, Evangelos Sigalas, Nitish V. Thakor, Anastasios Bezerianos, Junhua Li:
Boosting Transfer Learning Improves Performance of Driving Drowsiness Classification Using EEG. PRNI 2018: 1-4 - [i10]Jinshi Yu, Guoxu Zhou, Andrzej Cichocki, Shengli Xie:
Learning the Hierarchical Parts of Objects by Deep Non-Smooth Nonnegative Matrix Factorization. CoRR abs/1803.07226 (2018) - 2017
- [j25]Yu Zhang, Guoxu Zhou, Jing Jin, Yangsong Zhang, Xingyu Wang, Andrzej Cichocki:
Sparse Bayesian multiway canonical correlation analysis for EEG pattern recognition. Neurocomputing 225: 103-110 (2017) - [i9]Yuning Qiu, Guoxu Zhou, Kan Xie:
Deep Approximately Orthogonal Nonnegative Matrix Factorization for Clustering. CoRR abs/1711.07437 (2017) - 2016
- [j24]Yu Zhang, Guoxu Zhou, Qibin Zhao, Andrzej Cichocki, Xingyu Wang:
Fast nonnegative tensor factorization based on accelerated proximal gradient and low-rank approximation. Neurocomputing 198: 148-154 (2016) - [j23]Guoxu Zhou, Qibin Zhao, Yu Zhang, Tülay Adali, Shengli Xie, Andrzej Cichocki:
Linked Component Analysis From Matrices to High-Order Tensors: Applications to Biomedical Data. Proc. IEEE 104(2): 310-331 (2016) - [j22]Qibin Zhao, Guoxu Zhou, Liqing Zhang, Andrzej Cichocki, Shun-ichi Amari:
Bayesian Robust Tensor Factorization for Incomplete Multiway Data. IEEE Trans. Neural Networks Learn. Syst. 27(4): 736-748 (2016) - [j21]Yu Zhang, Guoxu Zhou, Jing Jin, Qibin Zhao, Xingyu Wang, Andrzej Cichocki:
Sparse Bayesian Classification of EEG for Brain-Computer Interface. IEEE Trans. Neural Networks Learn. Syst. 27(11): 2256-2267 (2016) - [j20]Guoxu Zhou, Andrzej Cichocki, Yu Zhang, Danilo P. Mandic:
Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction. IEEE Trans. Neural Networks Learn. Syst. 27(11): 2426-2439 (2016) - [c11]Yu Zhang, Qibin Zhao, Guoxu Zhou, Jing Jin, Xingyu Wang, Andrzej Cichocki:
Removal of EEG artifacts for BCI applications using fully Bayesian tensor completion. ICASSP 2016: 819-823 - [i8]Qibin Zhao, Guoxu Zhou, Shengli Xie, Liqing Zhang, Andrzej Cichocki:
Tensor Ring Decomposition. CoRR abs/1606.05535 (2016) - 2015
- [j19]Bo Li, Guoxu Zhou, Andrzej Cichocki:
Two Efficient Algorithms for Approximately Orthogonal Nonnegative Matrix Factorization. IEEE Signal Process. Lett. 22(7): 843-846 (2015) - [j18]Andrzej Cichocki, Danilo P. Mandic, Lieven De Lathauwer, Guoxu Zhou, Qibin Zhao, Cesar F. Caiafa, Anh Huy Phan:
Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis. IEEE Signal Process. Mag. 32(2): 145-163 (2015) - [j17]Guoxu Zhou, Andrzej Cichocki, Qibin Zhao, Shengli Xie:
Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness. IEEE Trans. Image Process. 24(12): 4990-5003 (2015) - [c10]Guoxu Zhou, Andrzej Cichocki, Danilo P. Mandic:
Common components analysis via linked blind source separation. ICASSP 2015: 2150-2154 - [i7]Guoxu Zhou, Qibin Zhao, Yu Zhang, Tülay Adali, Shengli Xie, Andrzej Cichocki:
Linked Component Analysis from Matrices to High Order Tensors: Applications to Biomedical Data. CoRR abs/1508.07416 (2015) - 2014
- [j16]Yu Zhang, Guoxu Zhou, Jing Jin, Qibin Zhao, Xingyu Wang, Andrzej Cichocki:
Aggregation of Sparse Linear Discriminant analyses for Event-Related potential Classification in Brain-Computer Interface. Int. J. Neural Syst. 24(1) (2014) - [j15]Yu Zhang, Guoxu Zhou, Jing Jin, Xingyu Wang, Andrzej Cichocki:
Frequency Recognition in SSVEP-Based BCI using Multiset Canonical Correlation Analysis. Int. J. Neural Syst. 24(4) (2014) - [j14]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. Int. J. Neural Syst. 24(8) (2014) - [j13]Guoxu Zhou, Andrzej Cichocki, Qibin Zhao, Shengli Xie:
Nonnegative Matrix and Tensor Factorizations : An algorithmic perspective. IEEE Signal Process. Mag. 31(3): 54-65 (2014) - [c9]Qibin Zhao, Guoxu Zhou, Liqing Zhang, Andrzej Cichocki:
Tensor-variate Gaussian processes regression and its application to video surveillance. ICASSP 2014: 1265-1269 - [c8]Guoxu Zhou, Qibin Zhao, Yu Zhang, Andrzej Cichocki:
Fast Nonnegative Tensor Factorization by Using Accelerated Proximal Gradient. ISNN 2014: 459-468 - [i6]Andrzej Cichocki, Danilo P. Mandic, Anh Huy Phan, Cesar F. Caiafa, Guoxu Zhou, Qibin Zhao, Lieven De Lathauwer:
Tensor Decompositions for Signal Processing Applications From Two-way to Multiway Component Analysis. CoRR abs/1403.4462 (2014) - [i5]Guoxu Zhou, Andrzej Cichocki, Qibin Zhao, Shengli Xie:
Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness. CoRR abs/1404.4412 (2014) - [i4]Qibin Zhao, Guoxu Zhou, Liqing Zhang, Andrzej Cichocki, Shun-ichi Amari:
Robust Bayesian Tensor Factorization for Incomplete Multiway Data. CoRR abs/1410.2386 (2014) - [i3]Guoxu Zhou, Andrzej Cichocki, Shengli Xie:
Decomposition of Big Tensors With Low Multilinear Rank. CoRR abs/1412.1885 (2014) - 2013
- [j12]Qibin Zhao, Guoxu Zhou, Tülay Adali, Liqing Zhang, Andrzej Cichocki:
Kernelization of Tensor-Based Models for Multiway Data Analysis: Processing of Multidimensional Structured Data. IEEE Signal Process. Mag. 30(4): 137-148 (2013) - [j11]Guoxu Zhou, Andrzej Cichocki, Shengli Xie:
Accelerated Canonical Polyadic Decomposition Using Mode Reduction. IEEE Trans. Neural Networks Learn. Syst. 24(12): 2051-2062 (2013) - [c7]Qibin Zhao, Guoxu Zhou, Tülay Adali, Liqing Zhang, Andrzej Cichocki:
Kernel-based tensor partial least squares for reconstruction of limb movements. ICASSP 2013: 3577-3581 - 2012
- [j10]Guoxu Zhou, Andrzej Cichocki:
Canonical Polyadic Decomposition Based on a Single Mode Blind Source Separation. IEEE Signal Process. Lett. 19(8): 523-526 (2012) - [j9]Shengli Xie, Liu Yang, Jun-Mei Yang, Guoxu Zhou, Yong Xiang:
Time-Frequency Approach to Underdetermined Blind Source Separation. IEEE Trans. Neural Networks Learn. Syst. 23(2): 306-316 (2012) - [j8]Guoxu Zhou, Andrzej Cichocki, Shengli Xie:
Fast Nonnegative Matrix/Tensor Factorization Based on Low-Rank Approximation. IEEE Trans. Signal Process. 60(6): 2928-2940 (2012) - [c6]Guoxu Zhou, Zhaoshui He, Yu Zhang, Qibin Zhao, Andrzej Cichocki:
Canonical Polyadic Decomposition: From 3-way to N-Way. CIS 2012: 391-395 - [c5]Yu Zhang, Qibin Zhao, Guoxu Zhou, Xingyu Wang, Andrzej Cichocki:
Regularized CSP with Fisher's criterion to improve classification of single-trial ERPs for BCI. FSKD 2012: 891-895 - [c4]Fengyu Cong, Guoxu Zhou, Qibin Zhao, Qiang Wu, Asoke K. Nandi, Tapani Ristaniemi, Andrzej Cichocki:
Sequential nonnegative tucker decomposition on multi-way array of time-frequency transformed event-related potentials. MLSP 2012: 1-6 - [i2]Guoxu Zhou, Andrzej Cichocki, Shengli Xie:
Accelerated Canonical Polyadic Decomposition by Using Mode Reduction. CoRR abs/1211.3500 (2012) - [i1]Guoxu Zhou, Andrzej Cichocki, Shengli Xie:
Common and Individual Features Analysis: Beyond Canonical Correlation Analysis. CoRR abs/1212.3913 (2012) - 2011
- [j7]Zuyuan Yang, Guoxu Zhou, Shengli Xie, Shuxue Ding, Jun-Mei Yang, Jun Zhang:
Blind Spectral Unmixing Based on Sparse Nonnegative Matrix Factorization. IEEE Trans. Image Process. 20(4): 1112-1125 (2011) - [j6]Guoxu Zhou, Zuyuan Yang, Shengli Xie, Jun-Mei Yang:
Mixing Matrix Estimation From Sparse Mixtures With Unknown Number of Sources. IEEE Trans. Neural Networks 22(2): 211-221 (2011) - [j5]Guoxu Zhou, Zuyuan Yang, Shengli Xie, Jun-Mei Yang:
Online Blind Source Separation Using Incremental Nonnegative Matrix Factorization With Volume Constraint. IEEE Trans. Neural Networks 22(4): 550-560 (2011) - [j4]Guoxu Zhou, Shengli Xie, Zuyuan Yang, Jun-Mei Yang, Zhaoshui He:
Minimum-Volume-Constrained Nonnegative Matrix Factorization: Enhanced Ability of Learning Parts. IEEE Trans. Neural Networks 22(10): 1626-1637 (2011) - [j3]Zhaoshui He, Shengli Xie, Rafal Zdunek, Guoxu Zhou, Andrzej Cichocki:
Symmetric Nonnegative Matrix Factorization: Algorithms and Applications to Probabilistic Clustering. IEEE Trans. Neural Networks 22(12): 2117-2131 (2011) - [c3]Yu Zhang, Guoxu Zhou, Qibin Zhao, Akinari Onishi, Jing Jin, Xingyu Wang, Andrzej Cichocki:
Multiway Canonical Correlation Analysis for Frequency Components Recognition in SSVEP-Based BCIs. ICONIP (1) 2011: 287-295
2000 – 2009
- 2009
- [j2]Shengli Xie, Guoxu Zhou, Zuyuan Yang, Yuli Fu:
On Blind Separability Based on the Temporal Predictability Method. Neural Comput. 21(12): 3519-3531 (2009) - [j1]Guoxu Zhou, Shengli Xie, Zuyuan Yang, Jun Zhang:
Nonorthogonal Approximate Joint Diagonalization With Well-Conditioned Diagonalizers. IEEE Trans. Neural Networks 20(11): 1810-1819 (2009) - [c2]Min Zhao, Weijun Li, Guoxu Zhou, Zhiheng Zhou:
Blind Sources Separation Algorithm Based on Adaptive Givens Rotations. ICNC (1) 2009: 95-99 - [c1]Zuyuan Yang, Guoxu Zhou, Shengli Xie:
Blind Extraction Using Fractional Lower-Order Statistics. ICNC (6) 2009: 569-572
Coauthor Index
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