最终学位：博士
导师类型：硕士生导师
电子邮箱：ykx@sxu.edu.cn
联系电话：0351-7010566
研究方向：机器学习与数据挖掘等
姚凯旋，博士，讲师，2023年博士毕业于澳门新甫京娱乐娱城平台澳门新甫京娱乐娱城平台，研究方向为机器学习与数据挖掘。在Artificial Intelligence、Pattern Recognition、Neural Networks、ACM WSDM等国内外期刊和会议发表论文多篇。曾获2022年宝钢教育基金优秀学生奖、山西省优秀博士学位论文奖、2022年CCF优秀大学生学术秀（博士组）二等奖、2023年ACM中国理事会太原分会优秀博士学位论文奖。担任《中国科学：信息科学》、IEEE TIP、IEEE TNNLS、ACM TKDD、Neural Networks、NeurIPS、ICML、ICLR等期刊和会议的审稿人。团队招收对机器学习与数据挖掘感兴趣的硕士研究生，欢迎随时与我邮件联系。
[1] Kaixuan Yao, Jiye Liang, Jianqing Liang, Ming Li, Feilong Cao. Multi-view graph convolutional networks with attention mechanism. Artificial Intelligence, 2022, 307: 103708.
[2] Kaixuan Yao, Feilong Cao, Yee Leung, Jiye Liang. Deep neural network compression through interpretability-based filter pruning. Pattern Recognition, 2021, 119: 108056.
[3] Kaixuan Yao, Zijin Du, Ming Li, Feilong Cao, Jiye Liang. Robust graph neural networks with Dirichlet regularization and residual connection. International Journal of Machine Learning and Cybernetics, 2024.
[4] Shenggui Tang, Kaixuan Yao*, Jianqing Liang, Zhiqiang Wang, Jiye Liang. Graph neural networks with interlayer feature representation for image super-resolution. Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (ACM WSDM), 2023: 652-660.
[5] Feilong Cao, Kaixuan Yao, Jiye Liang. Deconvolutional neural network for image super-resolution. Neural Networks, 2020, 132: 394-404.
[6] Liangliang Wen, Jiye Liang, Kaixuan Yao, Zhiqiang Wang. Black-box adversarial attack on graph neural networks with node voting mechanism. IEEE Transactions on Knowledge and Data Engineering, 2024.
[7] Jiye Liang, Zijin Du, Jianqing Liang, Kaixuan Yao, Feilong Cao. Long and short-range dependency graph structure learning framework on point cloud. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.
[8] Zhihao Guo, Feng Wang, Kaixuan Yao, Jiye Liang, Zhiqiang Wang. Multi-scale variational graph autoencoder for link prediction. Proceedings of the Fifteenth ACM international conference on web search and data mining (ACM WSDM), 2022: 334-342.
[9] Jie Wang, Jianqing Liang, Jiye Liang, Kaixuan Yao. GUIDE: Training deep graph neural networks via guided dropout over edges. IEEE Transactions on Neural Networks and Learning Systems, 2022, 35(4): 4465-4477.
[10] Jie Wang, Jiye Liang, Kaixuan Yao, Jianqing Liang, Dianhui Wang. Graph convolutional autoencoders with co-learning of graph structure and node attributes. Pattern Recognition, 2022, 121: 108215.
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