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师资队伍

师资队伍

刘勇 准聘助理教授
副研究员、博士生导师。博士毕业于天津大学。从事机器学习研究,特别关注大规模机器学习、自动机器学习、统计机器学习理论等。在顶级期刊和会议上发表论文30余篇,其中以第一作者或通讯作者发表CCF A类文章15余篇,涵盖机器学习领域顶级期刊TPAMI、TNNLS和NeurIPS,ICML,IJCAI,AAAI机器学习4大顶级会议。曾获得中国科学院“青年创新促进会”会员以及中国科学院信息工程研究所“引进优秀人才”称号。担任NeurIPS、ICML、AAAI、IJCAI等多个重要的国际会议和期刊评审。

个人主页: https://iie-liuyong.github.io/; https://dblp.uni-trier.de/pid/29/4867-18.html

详细资料

工作经历

中国人民大学高人工智能学院,准聘助理教授, 2020年8月-至今

中国科学院信息工程研究所,副研究员,2018年10月-20207

中国科学院信息工程研究所,助理研究员,2016年7月-2018年10

研究方向

--大规模机器学习

--自动机器学习

--统计机器学习理论

对学生的培养要求

只有一个要求:努力的学生

科研项目

[1] 深度神经网络结构自动搜索理论与算法研究,90万,中国科学院基础前沿科学研究计划,2019.9-2024.9,负责人

[2] 大规模机器学习模型选择算法研究,中国科学院“青促会”人才项目,80万,2019.1-2022.12,负责人

[3] 基于积分算子谱分析的核方法模型选择,中国科学院信息工程研究所

引进优秀青年人才,40万,2017.1-2019.12,负责人

[4] 大规模核方法积分算子谱分析的模型选择方法,国家自然科学基金,24万,2018.1-2020.12,负责人

[5] 基于贝叶斯优化的DNN模型结构自动机器学习,2019.10-2020.9,15万,腾讯犀牛鸟基金,负责人

[6] 大数据和人工智能发展现状及趋势,保密局战略研究项目子课题,40万,2017.9-2020.12,子课题负责人

科研成果

- Yong Liu, Shizhong Liao, Shali Jiang, Lizhong Ding, Hailun Lin, Weiping Wang. Fast Cross-Validation for Kernel-based Algorithms,IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020,42(5):1083-1096. (CCF A)

- Rong Yin, Yong Liu, Lijing Lu, Weiping Wang, Dan Meng. Divide-and-Conquer Learning with Nyström: Optimal Rate and Algorithm. Proceedings of 34th Conference on Artificial Intelligence (AAAI), 2020: 6696-6703. (CCF A)

- Jian Li, Yong Liu, Weiping Wang. Automated Spectral Kernel Learning. In: Proceedings of 34th Conference on Artificial Intelligence (AAAI), 2020: 4618-4625. (CCF A)

- Lizhong Ding, Shizhong Liao, Yong Liu, Li Liu, Fan Zhu, Yazhou Yao, Ling Shao, Xin Gao. Approximate Kernel Selection via Matrix Approximation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020. (CCF B)

-Lizhong Ding, Mengyang Yu, Li Liu, Fan Zhu, Yong Liu, Yu Li, Ling Shao. Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test. Advances in Neural Information Processing Systems 32 (NeurIPS), 2019:11257-11268. (CCF A)

-Jian Li, Yong Liu, Rong Yin , Weiping Wang. Multi-Class Learning using Unlabeled Samples: Theory and Algorithm. Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019: 2880-2886. (CCF A)

-Jian Li, Yong Liu, Rong Yin, et al. Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis. Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019:2887-2893. (CCF A)

-Hua Zhang, Peng She, Yong Liu, Jianhou Gan, Xiaochun Cao, Hassan Foroosh. Learning Structural Representations via Dynamic Object Landmarks Discovery for Sketch Recognition and Retrieval. IEEE Transactions on Image Processing (TIP), 2019, 28(9):4486-4499. (CCF A)

-Lizhong Ding, Zhi Liu, Yu Li, Shizhong Liao, Yong Liu, Peng Yang, Ge Yu, Ling Shao, Xin Gao. Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data. Proceedings of 33th Conference on Artificial Intelligence (AAAI), 2019:3454-3461.

- Lizhong Ding, Yong Liu, Shizhong Liao, Yu Li, Peng Yang, Yijie Pan, Chao Huang, Ling Shao, Xin Gao. Approximate Kernel Selection with Strong Approximate Consistency. Proceedings of 33th Conference on Artificial Intelligence (AAAI), 2019: 3462-3469.

-Rong Yin, Yong Liu, Weiping Wang, et al. Sketch Kernel Ridge Regression using Circulant Matrix: Algorithm and Theory. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019. Online, DOI:10.1109/TNNLS.2019.2944959. (CCF B)

-Yong Liu, Shizhong Liao, Hua Zhang, et al. Kernel Stability for Model Selection in Kernel-based Algorithms. IEEE Transactions on Cybernetics (TCYB), 2019. Online, DOI: 10.1109/TCYB.2019.2923824. (CCF B)

-Jian Li, Yong Liu, Rong Yin, et al. Multi-Class Learning: From Theory to Algorithm. Advances in Neural Information Processing Systems 31 (NeurIPS), 1593-1602, 2018. (CCF A)

-Yong Liu, Hailun Lin, Lizhong Ding, et al. Fast Cross-Validation. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2910-2917, 2018. (CCF A)

-Lizhong Ding, Shizhong Liao, Yong Liu, Peng Yang, Xin Gao. Randomized Kernel Selection With Spectra of Multilevel Circulant Matrices. Proceedings of 32rd Conference on Artificial Intelligence (AAAI), 2018: 2910-2917.

-Yong Liu, Shizhong Liao, Linhai Lun, et al. Generalization Analysis for Ranking Using Integral Operator, Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017: 2273-2279. (CCF A)

-Yong Liu, Shizhong Liao, Hailun Lin, et al. Infinite Kernel Learning: Generalization Bounds and Algorithms. Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017, 2280-2286. (CCF A)

-Jian Li, Yong Liu, Hailun Lin. Efficient Kernel Selection via Spectral Analysis. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI), 2017: 2124-2130. (CCF A)

-Yong Liu, Shizhong Liao. Granularity selection for cross-validation of SVM. Information Sciences, 2017, 475-483. ( CCF B)

-刘勇,廖士中. 基于积分算子空间显示描述的框架核选择方法. 中国科学: 信息科学, 2016, 46(2), 165–178. (CCF A 中文期刊)

-Yong Liu, Shizhong Liao. Eigenvalues ratio for kernel selection of kernel methods. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015: 2814–2820. (CCF A)

-Yong Liu, Shali Jiang, Shizhong Liao. Efficient Approximation of Cross-validation for Kernel Methods using Bouligand Influence Function. In: Proceedings of The 31st International Conference on Machine Learning (ICML). 2014, 324-332. (CCF A)

-Yong Liu, Shizhong Liao. Kernel selection with spectral perturbation stability of kernel matrix. Science China Information Sciences, 2014, 57: 112103(10) (CCF B)

-刘勇,江沙里,廖士中. 基于近似高斯核显式描述的大规模 SVM 求解. 计算机研究与发展,2014, 51(10):2171-2177. (CCF A 中文期刊)

-Yong Liu, Shizhong Liao. Preventing Over-Fitting of Cross-Validation with Kernel Stability. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), 2014:290–305. (CCF B)

-Yong Liu, Shali Jiang, Shizhong Liao. Eigenvalues Perturbation of Integral operator for Kernel Selection. In: Proceedings of the 22nd ACM International Conference on Information and Knowledge management (CIKM), 2013:2189-2198. (CCF B)

-Yong Liu, Shizhong Liao, Yuexuan-Hou. Learning kernels with upper bounds of leave-one-out error. Proceedings of the 20th ACM International Conference on Information and Knowledge management (CIKM), 2011:2205-2208. (CCF B)

社会兼职

IJCAI 2020,IJCAI 2019 高级程序委员

NeurIPS 2020, 程序委员

AAAI 2020,程序委员

ICML 2019,程序委员

荣誉获奖

工作阶段

2019年中国科学院“青促会”人才称号

2017年中国科学院信息工程研究所“引进优秀人才”称号

博士期间

2012年博士研究生国家学术新人奖

Best Paper Award of The 2nd PAKDD Doctoral Symposium on Data Mining

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