Preprint

• 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.2020.0001602020.

• Kai Wu, Chao Wang, Jing Liu, “Network Collaborator: Knowledge Transfer Between Network Reconstruction and Community Detection,” Neurocomputing, Submitted, 2024.

• 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

2024

• Xiaoyu Zhang, Yulin Jin, Haoyu Tong, Jian Lou, Kai Wu, and Xiaofeng Chen, “Purifier^+: Plug-and-play Backdoor Mitigation for Pre-trained Models via Activation Alignment,” IEEE Transactions on Multimedia, accepted, 2024. (code)

• Xiaoyu Zhang, Chenyang Zhang, Jian Lou, Kai Wu, Zilong Wang, Xiaofeng Chen, “DuplexGuard: Safeguarding Deletion Right in Machine Unlearning via Duplex Watermarking,” IEEE Transactions on Dependable and Secure Computing, DOI: 10.1109/TDSC.2024.3456811, 2024.

• Yingzhi Teng, Kai Wu*, Jing Liu, Yifan Li, Xiangyi Teng “Constructing High-order Functional Connectivity Networks with Temporal Information from fMRI Data,” IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2024.3412399, 2024. (code)

• Yingzhi Teng, Jing Liu, Kai Wu, Kaixin Yuan “Time Series Prediction based on LSTM and High-Order Fuzzy Cognitive Map with Attention Mechanism,” Neural Processing Letters, accepted, 2024.

• Yingzhi Teng, Jing Liu, Kai Wu, Yang Liu, Baihao Qiao “Multivariate time series clustering based on fuzzy cognitive maps and community detection,” Neurocomputing, vol. 590, 127743, 2024.

• Yingzhi Teng, Kai Wu*, Jing Liu, “Causal Discovery from Abundant but Noisy Fuzzy Cognitive Map Set,” IEEE Transactions on Fuzzy Systems, vol. 32, no. 7, pp. 3992-4003, 2024. (code)

2023

• Yuanyuan Li, Kai Wu*, Jing Liu, “Discover governing differential equations from evolving systems,” Physical Review Research, vol. 5, 023126, 2023. (code)

• Huixin Ma, Kai Wu*, Handing Wang, Jing Liu, “Higher-order Knowledge Transfer for Dynamic Community Detection with Great Changes,” IEEE Transactions on Evolutionary Computation, vol. 28, no. 1, pp. 90-104, 2024. (code)

• Yitong Li, Kai Wu*, Jing Liu, “Self-paced ARIMA for Robust Time Series Prediction,” Knowledge-Based Systems, vol. 269, pp. 110489, 2023.

• Yilu Liu, Jing Liu, Kai Wu, “Cost-Effective Competition on Social Networks via Pareto Optimization,” Information Sciences, vol. 620, pp. 31-46, 2023.

• 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, vol. 18, no. 1, pp. 52-67, 2023. (code)

2022

• Kai Wu, Chao Wang*, Jing Liu, “Evolutionary multitasking multilayer network reconstruction,” IEEE Transactions on Cyberentics, vol. 52, no. 12, pp. 12854-12868, 2022. (code)

• 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)

• 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)

• 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, vol. 35, no. 4, pp. 4985-4998, 2024. (code)

• Kai Wu, Jing Liu*, “Learning large-scale fuzzy cognitive maps under limited resources,” Engineering Applications of Artificial Intelligence, vol. 116, pp. 105376, 2022.(code)

• 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)

• 李怡桐, 刘晓涛, 刘静, 吴凯, “基于加权局部复杂不变性的时间序列分类算法,” 系统仿真学报, DOI: 10.16182/j.issn1004731x.joss.21-0456, 2022, In Press.

2021

• 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)

• 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)

• 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)

• Chao Wang, Kai Wu*, Jing Liu, “Evolutionary Multitasking AUC optimization,” IEEE Computational Intelligence Magazine, vol. 17, no. 2, pp. 67-82, 2022. (code)

• 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, vol. 53, no. 4, pp. 2137-2510, 2023. (code)

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

• Chao Wang, Jing Liu*, Kai Wu, Zhaoyang Wu, “Solving multi-task optimization problems with adaptive knowledge transfer via anomaly detection,” IEEE Transactions on Evolutionary Computation, vol. 26, no. 2, pp. 304-318, 2022. (code)

• 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)

• 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.

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.

• 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.

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

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.

• 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.

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

• 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.

• 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.

• 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.

Conference Papers

• Kai Wu, Yujian Betterest Li*, Jian Lou, Xiaoyu Zhang, Handing Wang, Jing Liu, “Rapid Plug-in Defenders,” NeurIPS 2024.

• Xiaobin Li, Kai Wu*, Yujian Betterest Li, Xiaoyu Zhang, Handing Wang, Jing Liu, “Pretrained Optimization Model for Zero-Shot Black Box Optimization,” NeurIPS 2024

• Haoyu Tong, Xiaoyu Zhang, Jin Yulin, Jian Lou, Kai Wu, Xiaofeng Chen, “Balancing Generalization and Robustness in Adversarial Training via Steering through Clean and Adversarial Gradient Directions,” ACM MM 2024

• Xinyu Guo, Kai Wu*, Xiaoyu Zhang, Jing Liu, “Automated Loss function Search for Class-imbalanced Node Classification,” ICML 2024, 235:16958-16973.

• Yudong Yang, Kai Wu*, Xiangyi Teng, Handing Wang, He Yu, Jing Liu, “Exploring Knowledge Transfer in Evolutionary Many-task Optimization: A Complex Network Perspective,” GECCO 2024.

• Lanlan Chen, Kai Wu*, Jing Liu, “Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamics,” AAAI 2024, vol.38, no.8, pp. 8292-8301. (code)

• 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

• Kai Wu, Jing Liu*, Chao Wang, Kaixin Yuan, “Pareto optimization for influence maximization in social networks,” EMO2021, Shenzhan, China, 2021, pp. 697-707. (code)

• 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.

• Kai Wu, Jing Liu*, “Classification-based optimization with multi-fidelity evaluations,” Proceedings of IEEE Congress on Evolutionary Computation 2019 (IEEE CEC2019), Wellington, New Zealand, 2019, pp. 1126-1131.

• 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.

• 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.

• 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.