Publications

* stands for corresponding author, and # stands for co-first author.

Top conference papers

[1] Tommaso Salvatori‚ Yuhang Song*‚ Zhenghua Xu‚ Thomas Lukasiewicz and Rafal Bogacz. Reverse Differentiation via Predictive Coding. In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. (CCF Rank A, Acceptance rate: 15%)
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[2] Tommaso Salvatori#‚ Yuhang Song#*‚ Yujian Hong‚ Simon Frieder‚ Lei Sha‚ Zhenghua Xu‚ Rafal Bogacz and Thomas Lukasiewicz. Associative Memories via Predictive Coding. In Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS), 2021. (CCF Rank A, Acceptance rate: 26%)
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[3] Jianfeng Wang, Thomas Lukasiewicz‚ Xiaolin Hu, Jianfei Cai, Zhenghua Xu*. RSG: A Simple But Effective Module for Learning Imbalanced Datasets. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021. (CCF Rank A, Acceptance rate: 27%)
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[4] Yixin Su, Rui Zhang*‚ Sarah Erfani, Zhenghua Xu*. Detecting Beneficial Feature Interactions for Recommender Systems. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (CCF Rank A, Acceptance rate: 21%)
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[5] Yuhang Song, Thomas Lukasiewicz‚ Zhenghua Xu*, Rafal Bogacz. Can the Brain Do Backpropagation? —— Exact Implementation of Backpropagation in Predictive Coding Networks. In Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020. (CCF Rank A, Acceptance rate: 20.09%)
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[6] Yuhang Song‚ Andrzej Wojcicki‚ Thomas Lukasiewicz‚ Jianyi Wang‚ Abi Aryan‚ Zhenghua Xu*‚ Mai Xu‚ Zihan Ding and Lianlong Wu. Arena: A General Evaluation Platform and Building Toolkit for Multi−Agent Intelligence. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF Rank A, Acceptance rate: 20.6%)
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[7] Yuhang Song‚ Jianyi Wang‚ Thomas Lukasiewicz‚ Zhenghua Xu*‚ Shangtong Zhang‚ Andrzej Wojcicki and Mai Xu. Mega−Reward: Achieving Human−Level Play without Extrinsic Rewards. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (CCF Rank A, Acceptance rate: 20.6%)
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[8] Yuhang Song#, Jianyi Wang#, Thomas Lukasiewicz, Zhenghua Xu* and Mai Xu. Diversity-Driven Extensible Hierarchical Reinforcement Learning. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019. (CCF Rank A, Acceptance rate: 16.2%)
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[9] Zhenghua Xu*, Thomas Lukasiewicz, Cheng Chen*, Yishu Miao and Xiangwu Meng. Tag-Aware Personalized Recommendation Using a Hybrid Deep Model. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2017. (CCF Rank A, Acceptance rate: 25.9%)
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[10] Andy Yuan Xue, Rui Zhang, Yu Zheng, Xing Xie, Jin Huang and Zhenghua Xu*. Destination Prediction by Sub-trajectory Synthesis and Privacy Protection against Such Prediction. In Proceedings of the 29th IEEE International Conference on Data Engineering (ICDE), 2013. (CCF Rank A, Acceptance rate: 19.8%, Number of Google Scholar citaions: 300)
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[11] Zhenghua Xu*#, Di Yuan#, Thomas Lukasiewicz, Cheng Chen, Yishu Miao and Guizhi Xu*. Hybrid Deep-Semantic Matrix Factorization for Tag-Aware Personalized Recommendation. In Proceedings of the 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020. (CCF Rank B)
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[12] Zhenghua Xu#, Chang Qi# and Guizhi Xu*. Semi-Supervised Attention-Guided CycleGAN for Data Augmentation on Medical Images. In Proceedings of 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019. (CCF Rank B, Acceptance rate: 18%)
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[13] Lei Wang#, Bo Wang#, Zhenghua Xu*. Tumor Segmentation Based on Deeply Supervised Multi-Scale U-Net. In Proceedings of 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019. (CCF Rank B, Acceptance rate: 18%)
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[14] Bo Li#, Zehua Cheng#, Zhenghua Xu*, Wei Ye*, Thomas Lukasiewicz and Shikun Zhang. Long Text Analysis Using Sliced Recurrent Neural Networks with Breaking Point Information Enrichment. In Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019. (CCF Rank B)
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[15] Cheng Chen, Thomas Lukasiewicz, Xiangwu Meng and Zhenghua Xu (co-first author, in alphabetical order). Location-Aware News Recommendation Using Deep Localized Semantic Analysis. In Proceedings of the 22nd International Conference on Database Systems for Advanced Applications (DASFAA), 2017. (CCF Rank B, Acceptance rate: 24.3%)
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[16] Zhenghua Xu, Cheng Chen, Thomas Lukasiewicz, Yishu Miao and Xiangwu Meng. Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling. In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM),2016. (CCF Rank B, Acceptance rate: 28.8%)
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[17] Zhenghua Xu, Rui Zhang, Ramamohanarao Kotagiri and Udaya Parampalli. An Adaptive Online Algorithm for Time Series Segmentation with Error Bound Guarantee. In Proceedings of the 15th International Conference on Extending Database Technology (EDBT), 2012. (CCF Rank B, Acceptance rate: 22.5%)
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[18] Jianzhong Qi, Zhenghua Xu, Yuan Xue and Zeyi Wen. A Branch and Bound Method for Min-dist Location Selection Queries. In Proceedings of the 23rd Australasian Database Conference (ADC), 2012. (Runner-up for Best Paper award)
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Top journal papers

[19] Zhenghua Xu*, Shijie Liu, Di Yuan*, Lei Wang, Junyang Chen, Thomas Lukasiewicz, Zhigang Fu, Rui Zhang. ω-Net: Dual Supervised Medical Image Segmentation with Multi-Dimensional Self-Attention and Diversely-Connected Multi-Scale Convolution. Accepted to publish in Neurocomputing, 2022. (SCI Q1, IF: 5.719)
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[20] Haozhe Lin, Yushun Fan, Jia Zhang, Bing Bai, Zhenghua Xu, Thomas Lukasiewicz. Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks. IEEE Transactions on SERVICE COMPUTING (TSC), 2022. (SCI Q1, IF: 8.216)
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[21] Junyang Chen, Zhiguo Gong*, Wei Wang, Cong Wang*, Zhenghua Xu, Jianming Lv, Xueliang Li, Kaishun Wu, Weiwen Liu. Adversarial Caching Training: Unsupervised Inductive Network Representation Learning on Large-Scale Graphs. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021. (SCI Q1, IF: 10.451)
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Other papers

[22] Zihang Lei, Mengxi Jiang, Guangsong Yang, Tianmin Guan, Peng Huang, Yu Gu, Zhenghua Xu, Qiubo Ye. Towards Recurrent Neural Network with Multi-Path Feature Fusion for Signal Modulation Recognition. In Wireless Networks, 2022. (SCI JCR Q2)

[23] Mingfei Zhang, Zhoutao Yu, Zhenghua Xu*. Short-Term Load Forecasting Using Recurrent Neural Networks With Input Attention Mechanism and Hidden Connection Mechanism. In IEEE Access, 2020. (SCI JCR Q1)

[24] Qian Zhou, Yan Shi, Zhenghua Xu*, Ruowei Qu, and Guizhi Xu. Classifying Melanoma Skin Lesions Using Convolutional Spiking Neural Networks With Unsupervised STDP Learning Rule. In IEEE Access, 2020. (SCI JCR Q1)

[25] Zhenghua Xu, Oana Tifrea-Marciuska, Thomas Lukasiewicz, Maria Vanina Martinez, Gerardo I. Simari and Cheng Chen. Lightweight Tag-Aware Personalized Recommendation on the Social Web Using Ontological Similarity. In IEEE Access, 2018. (SCI JCR Q1)
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[26] Cheng Chen, Xiangwu Meng, Zhenghua Xu, and Thomas Lukasiewicz. Location-Aware Personalized News Recommendation With Deep Semantic Analysis. In IEEE Access, 2017. (SCI JCR Q1)
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[27] Zhenghua Xu, Thomas Lukasiewicz and Oana TifreaMarciuska. Improving Personalized Search on the Social Web Based on Similarities between Users. In Proceedings of the 8th International Conference on Scalable Uncertainty Management (SUM), 2014. (EI)
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[28] Zhenghua Xu, Xinghuo Yu, Yong Feng, Jiankun Hu, Zahir Tari and Fengling Han. A Multi-Module Anomaly Detection Scheme based on System Call Prediction. In Proceedings of the 8th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2013. (EI & ISTP)
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[29] Zhenghua Xu, Xinghuo Yu, Yong Feng, Jiankun Hu, Zahir Tari and Fengling Han. Top-k Future System Call Prediction Based Multi-Module Anomaly Detection System. In Proceedings of the 6th International Congress on Image and Signal Processing (CISP), 2013. (EI & ISTP)
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