Publications

Journal and Conference Papers:

• Deqing Wang. Doubly Accelerated Proximal Gradient for Nonnegative Tensor Decomposition. In: Le, X., Zhang, Z. (eds) Advances in Neural Networks – ISNN 2024. ISNN 2024. Lecture Notes in Computer Science, vol 14827. Springer, Singapore. pp. 55–65.
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• Deqing Wang and Guoqiang Hu. Accelerating regularized tensor decomposition using the alternating direction method of multipliers with multiple Nesterov’s extrapolations, Signal Processing. Volume 222, 2024. p.109532. (SCI, Impact Factor: 4.4)
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• Deqing Wang and Guoqiang Hu. Efficient nonnegative tensor decomposition using alternating direction proximal method of multipliers, Chinese Journal of Electronics. Volume 33, Issue 5, 2024. p.1308-1316. (SCI, Impact Factor: 1.2)
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• Deqing Wang, Zheng Chang and Fengyu Cong. Sparse nonnegative tensor decomposition using proximal algorithm and inexact block coordinate descent scheme, Neural Computing and Applications. Volume 33, Issue 24, 2021. p.17369-17387. (SCI, Impact Factor: 6.0)
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• Guoqiang Hu, Deqing Wang, Siwen Luo, et al. Frequency specific co-activation pattern analysis via sparse nonnegative tensor decomposition. Journal of Neuroscience Methods. Volume 362, 2021. p.109299. (SCI, Impact Factor: 3.0)
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• Deqing Wang and Fengyu Cong. An inexact alternating proximal gradient algorithm for nonnegative CP tensor decomposition, Science China Technological Sciences. Volume 64, Issue 9, 2021. p.1893-1906. (SCI, Impact Factor: 4.6)
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• Deqing Wang, Fengyu Cong, Tapani Ristaniemi. Higher-Order Nonnegative CANDECOMP/PARAFAC Tensor Decomposition Using Proximal Algorithm, in 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, May 12-17, 2019. p. 3457-3461.
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• Deqing Wang, Fengyu Cong, Tapani Ristaniemi. Sparse Nonnegative CANDECOMP/PARAFAC Decomposition in Block Coordinate Descent Framework: A Comparison Study, arXiv preprint arXiv:1812.10637. Dec. 2018. p.1-15.
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• Deqing Wang, Yongjie Zhu, Tapani Ristaniemi, et al. Extracting multi-mode ERP features using fifth-order nonnegative tensor decomposition, Journal of Neuroscience Methods. Volume 308, 2018. p.240-247. (SCI, Impact Factor: 3.0)
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• Deqing Wang, Xiaoyu Wang, Yongjie Zhu, et al. Increasing stability of EEG Components Extraction Using Sparsity Regularized Tensor Decomposition, in Advances in Neural Networks – ISNN 2018, T. Huang, et al., Editors. 2018, Springer International Publishing. p. 789-799.
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• Deqing Wang, Fengyu Cong, Qibin Zhao, et al. Exploiting ongoing EEG with multilinear partial least squares during free-listening to music. in 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP). 2016. p. 1-6.
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• Deqing Wang, Zengwu Liu, and Fengyu Cong. Wood Surface Quality Detection and Classification Using Gray Level and Texture Features, in Advances in Neural Networks – ISNN 2015, X. Hu, et al., Editors. 2015, Springer International Publishing. p. 248-257.
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• Deqing Wang, Tianxing Niu and Jiasheng Qu. Research of Communication Between Visual C++ and Kingview Based on ActiveX Control, Techniques of Automation and Applications, 11, 2014. p. 1-8.
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• Shicai Zhu, Lan Mu, Zhijun Liu and Deqing Wang. A survey of foreign warship magnetic field characteristic research and warship protection techniques, Ship Science and Technology, 09, 2014. p. 1-6.
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• Xiufen Ye, Deqing Wang. Texture Image Segmentation Combining Chan-Vese Model and Structure Tensor. In 2012 Annual Conference of College of Automation, Harbin Engineering University. Harbin, China. 2012. [In Chinese]
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Dissertations

Doctoral Dissertation:
Deqing Wang, Extracting Meaningful EEG Features Using Constrained Tensor Decomposition, University of Jyväskylä, Finland. December 2019.
Dissertation Download Press Release in English Press Release in Finnish

Master Dissertation:
Deqing Wang, Image Segmentation Based on Partial Difference Equations, Harbin Engineering University, Harbin, China. March 2012.
Dissertation in Chinese