FACULTY & RESEARCH

Yong Liu
Tenure-track Assistant Professor
Yong Liu is tenure-track faculty at Gaoling School of Artificial Intelligence, Renmin University of China. He obtained the PhD degree from Tian Jin University, supervised by Shizhong Liao. His research interests are mainly about machine learning, with special attention to large-scale machine learning, autoML, statistical machine learning theory, etc. He has published over 30 papers on top-tier conferences and journals in artificial intelligence, e.g., TPAMI, NeurIPS, ICML, IJCAI, AAAI, TIP, TNNLS, etc. He received the "Youth Innovation Promotion Association" of CAS and the "Excellent Talent Introduction" of Institute of Information Engineering, CAS. He served as the program committee of several conferences, e.g., NeurIPS, AAAI, IJCAI, ECAI etc.

Personal Homepage: https://iie-liuyong.github.io/; https://dblp.uni-trier.de/pid/29/4867-18.html

Detailed Information

Professional Experience

2020/8 -Now, Assistant Professor, Renmin University of China

2018/10-2020/7, Associate Researcher, Institute of Information Engineering, CAS

2016/7-2018/10, Assistant Researcher, Institute of Information Engineering, CAS

Research Interests

--Large-scale machine learning

-- Statistical Learning Theory

--AutoML

Requirements for Candidates

There is only one requirement: hardworking students.

Publication

- 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.

- 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.

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

- 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.

-Rong Yin, Yong Liu, Weiping Wang, Dan Meng. Extremely Sparse Johnson-Lindenstrauss Transform:From Theory to Algorithm. Proceedings of the 20th IEEE International Conference on Data Mining (ICDM), 2020.

-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.

-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.

-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.

-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.

-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.

-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.

-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.

-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.

-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.

-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.

-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.

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

-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.

-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.

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

-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.

-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.

-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.

Services

1、SeniorProgram Committee of Conference: IJCAI 2020,2021

2、Program Committee of Conference: NeurIPS 2020, AAAI 2021, ECAI 2020

Awards

2019"Youth Innovation Promotion Association" of CAS

2017 "Excellent Talent Introduction" of Institute of Information Engineering, CAS

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


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