Network Sciences

Preprint

• Huixin Ma, Kai Wu*, Handing Wang, Jing Liu, Higher-order Knowledge Transfer for Dynamic Community Detection with Great Changes, IEEE TEVC, Under Scond Review, 2022.

• Kai Wu, Intelligent Modeling Algorithm for Complex System and its Application (复杂系统智能建模算法及其应用研究), _Doctoral Dissertation, DOI:10.27389/d.cnki.gxadu.2020.000160_2020.

• Kai Wu, Chao Wang, Jing Liu, Network Collaborator: Knowledge Transfer Between Network Reconstruction and Community Detection, IEEE TAI, Submitted, 2022. [Code] [Paper]

• Lanlan Chen, Kai Wu*, Jian Lou, Jing Liu, Neural Dynamics on Signed Graph, AAAI 2023, Under Review, 2022.

• Ziang Xie, Kai Wu*, Jian Lou, Hongyang Chen, Jing Liu, Silencer: Robust Community Detection by Silencing of Noisy Links, IEEE TNNLS, submitted, 2022.

• Yingzhi Teng, Kai Wu*, Jing Liu, Learning fuzzy cognitive maps from abundant but noisy data, ASOC, submitted, 2022.

• Yingzhi Teng, Jing Liu, Kai Wu, Yang Liu, Multivariate Time Series Clustering based on Fuzzy Cognitive Maps and Community Detection, KBS, submitted, 2021.

• Fang Shen, Jing Liu, Kai Wu, A Sparse Multiagent Genetic Algorithm for Reconstructing Complex Networks from Time Series, IEEE TCy, submitted, 2021.

• Yingzhi Teng, Jing Liu, Kai Wu, Yang Liu, Time Series Prediction based on LSTM and High-Order Fuzzy Cognitive Map with Attention Mechanism, SOCO, submitted, 2021.

• Shanchao Yang, Jing Liu, Kai Wu, Mingming Li, Learn to generate time series conditioned graphs with generative adversarial nets, arXiv preprint arXiv:2003.01436, 2020.

Journal Papers

2022

• Yilu Liu, Jing Liu, Kai Wu, Cost-Effective Competition on Social Networks via Pareto Optimization, Information Sciences, accepted, 2022. [Paper]

• Chao Wang, Jiaxuan Zhao, Lingling Li, Licheng Jiao, Jing Liu, Kai Wu, A Multi-Transformation Evolutionary Framework for Influence Maximization in Social Networks, IEEE Computational Intelligence Magazine, accepted, 2022. [Code] [Paper]

• Kaixin Yuan, Kai Wu*, Jing Liu, Is Single Enough? A Joint Spatiotemporal Feature Learning Framework for Multivariate Time Series Prediction, IEEE Transactions on Neural networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3216107, 2022. [Code] [Paper]

• Kai Wu, Jing Liu*, Learning large-scale fuzzy cognitive maps under limited resources, Engineering Applications of Artificial Intelligence, vol. 116, pp. 105376, 2022. [Code] [Paper]

• Kai Wu, Kaixin Yuan*, Yingzhi Teng, Jing Liu, Licheng Jiao, Broad fuzzy cognitive map systems for time series classification, Applied Soft Computing, vol. 128, pp. 109458, 2022. [Code] [Paper]

2021

• Kai Wu, Chao Wang*, Jing Liu, Evolutionary multitasking multilayer network reconstruction, IEEE Transactions on Cyberentics, 2021, DOI: 10.1109/TCYB.2021.3090769, In Press. [Code] [Paper]

• Kai Wu, Chao Wang, Jing Liu, Multilayer nonlinear dynamical network reconstruction from streaming data, SCIENTIA SINICA Technologica, vol. 52, no. 6, pp. 971-982, 2022. [Code] [Paper]

• Kai Wu, Xingxing Hao*, Jing Liu, Penghui Liu, Fang Shen, Online reconstruction of complex networks from streaming data, IEEE Transactions on Cybernetics, vol. 52, no. 6, pp. 5136-5147, 2022. [Code] [Paper]

• Kai Wu, Jing Liu*, Xingxing Hao, Penghui Liu, Fang Shen, An evolutionary multi-objective framework for complex network reconstruction using community structure, IEEE Transactions on Evolutionary Computation, vol. 25, no. 2, pp. 247-261, 2021. [Code] [Paper]

• Kai Wu, Jing Liu*, Penghui Liu, Fang Shen, Online fuzzy cognitive map learning, IEEE Transactions on Fuzzy Systems, vol. 29, no. 7, pp. 1885-1898, 2021. [Code] [Paper]

• Kai Wu, Jing Liu*, Penghui Liu, Shanchao Yang, Time series prediction using sparse autoencoder and high-order fuzzy cognitive maps, IEEE Transactions on Fuzzy Systems, vol. 28, no. 12, pp. 3110-3121, 2021. [Code] [Paper]

• Chaolong Ying, Jing Liu*, Kai Wu, Chao, Wang, A multiobjective evolutionary approach for solving large-scale network reconstruction problems via logistic principal component analysis, IEEE Transactions on Cyberentics, 2021, DOI: 10.1109/TCYB.2021.3109914, In Press, [Code] [Paper]

• Fang Shen, Jing Liu*, Kai Wu, Evolutionary Multitasking network reconstruction from time series with online parameter estimation, Knowledge-based Systems, vol. 222, 107019, 2021. [Paper]

• Kaixin Yuan, Jing Liu*, Shanchao Yang, Kai Wu, Fang Shen, Time series forecasting based on kernel mapping and high-order fuzzy cognitive maps, Knowledge-based Systems, vol. 206, 106359, 2020. [Code] [Paper]

• Fang Shen, Jing Liu*, Kai Wu, Multivariate time series forecasting based on elastic net and high-order fuzzy cogitive maps: A case study on human action prediction through EEG signals, IEEE Transactions on Fuzzy Systems, vol. 29, no. 8, pp. 2336-2348, 2021. [Paper]

2020

• Fang Shen, Jing Liu*, Kai Wu, A preference-based evolutionary bi-objective approach for learning large-scale fuzzy cognitive maps: An application to gene regulatory network reconstruction, IEEE Transactions on Fuzzy Systems, vol. 28, no. 6, pp. 1035-1049, 2020. [Paper]

• Penghui Liu, Jing Liu*, Kai Wu, CNN-FCM: system modeling promotes stablity of deep learning in time series prediction, Knowledge-based Systems, vol. 203, 106081, 2020. [Paper]

• Fang Shen, Jing Liu*, Kai Wu, Evolutionary multitasking fuzzy cognitive map learning, Knowledge-Based Systems, vol. 192, pp. 105294, 2020. [Paper]

2016-2019

• Kai Wu, Jing Liu*, Dan Chen, Network reconstruction based on time series via memetic algorithm, Knowledge-Based Systems, vol. 164, pp. 404-425, 2019. [Paper]

• Kai Wu, Jing Liu*, Learning large-scale fuzzy cognitive maps based on compressed sensing and application in reconstructing gene regulatory networks, IEEE Transactions on Fuzzy Systems, vol. 25, no. 6, pp. 1546-1560, 2017. [Paper]

• Kai Wu, Jing Liu*, Yaxiong Chi, Wavelet fuzzy cognitive maps, Neurocomputing, vol. 232, pp. 94-103, 2017. [Paper]

• Kai Wu, Jing Liu*, Shuai Wang, Reconstructing networks from profit sequences in evolutionary games via a multiobjective optimization approach with lasso initialization, Scientific Reports, vol. 6, pp. 37771, 2016. [Paper]

• Kai Wu, Jing Liu*, Robust learning of large-scale fuzzy cognitive maps via the lasso from noisy time series, Knowledge-Based Systems, vol. 113, pp. 23-38, 2016. [Paper]

• Zhangtao Li, Jing Liu*, Kai Wu, A multiobjective evolutionary algorithm based on structural and attribute similarities for community detection in attributed networks, IEEE Transactions on Cybernetics, vol. 48, no. 7, pp.1963-1976, 2018. [Paper]

Conference Papers

2022

• Kai Wu, Xiangyi Teng*, Jing Liu, Locating hidden sources in evolutionary games based on fuzzy cognitive map, ChineseCSCW 21: Proceedings of the 16th Chinese Conference on Computer Supported Cooperative Work and Social Computing accepted. [Paper]

2021

• Kai Wu, Jing Liu*, Chao Wang, Kaixin Yuan, Pareto optimization for influence maximization in social networks, EMO2021, Shenzhan, China, 2021, pp. 697-707. [Code] [Paper]

2020

• Kai Wu, Jing Liu*, Multi-objective evolutionary top rank optimization with Pareto ensemble, Proceedings of 2020 IEEE Symposium Series on Computational Intelligence (IEEE SSCI2020), Canberra, ACT, Australia, 2020, pp. 624-630. [Paper]

2016-2020

• Kai Wu, Jing Liu*, Evolutionary game network reconstruction by memetic algorithm with l1/2 regularization, 2017 Asia-Pacific Conference on Simulated Evolution and Learning, Shenzhen, China, 2017, pp. 385-396. [Paper]

• Kai Wu, Jing Liu*, Learning of sparse fuzzy cognitive maps using evolutionary algorithm with lasso initialization, 2017 Asia-Pacific Conference on Simulated Evolution and Learning, Shenzhen, China, 2017, pp. 966-973. [Paper]

• Ze Yang, Jing Liu*, Kai Wu, Learning of boosting fuzzy cognitive maps using a real-coded genetic algorithm, Proceedings of IEEE Congress on Evolutionary Computation 2019 (IEEE CEC2019), Wellington, New Zealand, 2019, PP. 490-498. [Paper]

Survey Papers and Books