刘斌，本科硕士博士分别就读于辽宁工业大学信息与计算科学，电子科技大学软件工程和电子科技大学计算机软件与理论，并在英属哥伦比亚大学进行博士联合培养年，香港大学博士后，于2018年加入威斯尼斯ww2299mc棋牌。研究兴趣为机器 学习和数据挖掘。

研究方向：机器学习，自然语言处理，数据挖掘

Email: liubin@swufe.edu.cn

教授课程

机器学习、凸优化、Python程序设计

学术成果

1. Liu, Bin, Xiaoxue Gao, Mengshuang He, Fengmao Lv, and Guosheng Yin. "Online COVID-19 diagnosis with chest CT images: Lesion-attention deep neural networks." medRxiv (2020). doi: https://doi.org/10.1101/2020.05.11.20097907

2. Bin Liu and Guo sheng Yin. 2020. Chinese document classification with bi-directional convolutional language model. In Proceedings of the 43rd Inter-national ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ’20), July 25–30, 2020, Virtual Event, China. https://doi.org/10.1145/3397271.3401248

3. Zheng, Liyuan, Yajie Hu, Bin Liu*, and Wei Deng. "Learning robust word representation over a semantic manifold." Knowledge-Based Systems, no. 192 (2020): 105358.

4. Huang, Qian, Bin Liu*, Ningshe Zhao, Zhiyong Zhang, Qiurong Wang, Xiaoli Zhang, Yang Xun, Xiaoyu Ge, Jianlan Ding, and Sai-fu Fung. "Modeling for Professional Athletes’ Social Networks Based on Statistical Machine Learning." IEEE Access (2019).

5. Dan Ma, Bin Liu, Zhao Kang, Jiayu Zhou, Jianke Zhu, and Zenglin Xu*. "Two birds with one stone: Transforming and generating facial images with iterative GAN." Neurocomputing (2019).

6. Bin Liu, Lirong He, Yingming Li, Shandian Zhe, and Zenglin Xu*. "Neuralcp: Bayesian multiway data analysis with neural tensor decomposition." Cognitive Computation 10, no. 6 (2018): 1051-1061.

7. Bin Liu, Guosheng Yin, and Wenbin Du. "Text classification with pixel embedding." arXiv preprint arXiv:1911.04115 (2019).

8. Lirong He, Bin Liu, Guangxi Li, Yongpan Sheng, Yafang Wang, and Zenglin Xu*. "Knowledge base completion by variational bayesian neural tensor decomposition." Cognitive Computation 10, no. 6 (2018): 1075-1084.

9. Zenglin Xu, Bin Liu*, Shandian Zhe, Haoli Bai, Zihan Wang, and Jennifer Neville. "Variational random function model for network modeling." IEEE transactions on neural networks and learning systems 30, no. 1 (2019): 318-324.

10. Bin Liu, Yingming Li, and Zenglin Xu*. "Manifold regularized matrix completion for multi-label learning with ADMM." Neural Networks 101 (2018): 57-67.

11. Bin Liu, Dan Ma, Chunmei Ma, and Shuang Wu. "Gene functional annotation via matrix completion." In 2017 IEEE International Conference on Communications (ICC), pp. 1-6. IEEE, 2017.

12. Liqiang Wang, Yafang Wang, Bin Liu, Lirong He, Shijun Liu, Gerard De Melo, and Zenglin Xu. "Link prediction by exploiting network formation games in exchangeable graphs." In 2017 International Joint Conference on Neural Networks (IJCNN), pp. 619-626. IEEE, 2017.

13. Bin Liu, Zenglin Xu, Bo Dai, Haoli Bai, Xianghong Fang, Yazhou Ren, and Shandian Zhe. "Learning from semantically dependent multi-tasks." In 2017 International Joint Conference on Neural Networks (IJCNN), pp. 3498-3505. IEEE, 2017.

14. Haoli Bai, Zenglin Xu, Bin Liu, and Yingming Li. "Hierarchical Probabilistic Matrix Factorization with Network Topology for Multi-relational Social Network." In Asian Conference on Machine Learning, pp. 270-285. 2016.

15. Bin Liu, Zenglin Xu*, Shuang Wu, and Fei Wang. "Manifold regularized matrix completion for multilabel classification." Pattern Recognition Letters 80 (2016): 58-63.

16. Chunmei Ma*, Qing Zhu, Shuang Wu, and Bin Liu. "Representation Learning from Time Labelled Heterogeneous Data for Mobile Crowdsensing." Mobile Information Systems 2016 (2016):1-10.

17. Bin Liu, Chao Song, Ming Liu, and Nianbo Liu. "Distinguishing uncertain objects with multiple features for crowdsensing." In 2014 IEEE Global Communications Conference, pp. 2751-2756. IEEE, 2014.

18. Bin Liu, Chao Song, Ming Liu, Nianbo Liu, and Jinqi Zhu. "Understanding Multiple Features with Hypercube for Distinguishing Uncertain Objects in Mobile Crowdsensing." In 2014 IEEE 11th International Conference on Mobile Ad Hoc and Sensor Systems, pp. 247-251. IEEE, 2014.

学术兼职

Neurocomputing，Neural Networks 审稿人