中文简介

刘勇 男 副研究员 中国科学院信息工程研究所 电子邮箱:liuyong@iie.ac.cn

对机器学习领域中的核方法模型选择、大规模核方法等开展了深入研究,在顶级期刊和会议上发表论文20余篇,其中以第一作者或通讯作者发表CCFA类文章10余篇,涵盖机器学习领域顶级期刊T-PAMI和全部4大顶级会议(NIPS,ICML,IJCAI,AAAI)。获得中科院“青促会”和信工所“引进优青”人才称号及天津大学优秀博士论文。主持国家自然科学基金青年项目1项,中科院“青促会”和信工所“引进优青”人才项目2项,保密局战略研究项目子课题1项,作为核心骨干参与国家重点研发计划子课题和北京市局横向项目2项。

研究方向

大规模机器学习,模型选择,核方法

教育背景

2011-2016,天津大学计算机应用专业,博士生,导师:廖士中
2009-2011,天津大学计算机科学与技术专业,硕士生,导师:廖士中
2005-2009,河北工业大学信息与计算科学专业,本科生

工作经历

2016.7-2018.12,中国科学院信息工程研究所,助理研究员
2018.12-至今,中国科学院信息工程研究所,副研究员

荣誉称号

  • 中科院“青促会”人才称号,2019
  • 中国科学院信息工程研究所“引进优秀青年人才”,2017
  • 天津大学优秀博士毕业论文,2017
  • Best Paper Award of the 2nd PAKDD Doctoral Symposium on Data Mining
  • Student Travel Grant Award of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining

主持项目

  • 大规模核方法积分算子谱分析的模型选择方法,青年自然科学基金,2018.01–2020.12 (No.61703396)
  • 大规模核方法模型选择研究,中国科学院信息工程研究所“引进优秀青年人才”项目,2018.01-2020.12
  • 中科院“青促会”人才项目,2019-2022

文章列表

Learning Structural Representations via Dynamic Object Landmarks Discovery for Sketch Recognition and Retrieval
Hua Zhang, Peng She, Yong Liu, Xiaochun Cao, Hassan Foroosh. IEEE Transactions on Image Processing (TIP), 2019

Representation Learning of Taxonomies for Taxonomy Matching
Hailun Lin, Yong Liu*. International Conference on Computational Science (ICCS), 2019.

Efficient Cross-Validation for Semi-Supervised Learning
Yong Liu, Jian Li, Guangjun Wu, Lizhong Ding, Weiping Wang. arXiv, 2019.

Fast Cross-Validation for Kernel-based Algorithms
Yong Liu, Shizhong Liao, Shali Jiang, Lizhong Ding, Hailun Lin, Weiping Wang. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019, to appear.

Max-Diversity Distributed Learning: Theory and Algorithms
Yong Liu, Jian Li, Weiping Wang. arXiv, 2018.

Multi-Class Learning: From Theory to Algorithm
Jian Li, Yong Liu*, Rong Yin, Hua Zhang, Li-zhong Ding, Weiping Wang. Advances in Neural Information Processing Systems 31 (NIPS), 1593–1602, 2018.

Fast Cross-Validation
Yong Liu, Hailun Lin, Lizhong Ding, Weiping Wang, Shizhong Liao. Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2910-2917, 2018

Generalization Analysis for Ranking Using Integral Operator
Yong Liu, Shizhong Liao, Hailun Lin, Yinliang Yue, Weiping Wang. Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2272-2279, 2017

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

Efficient Kernel Selection via Spectral Analysis
Jian Li, Yong Liu*, Hailun Lin, Yinliang Yue, Weiping Wang. Procedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2124-2130, 2017.

Eigenvalues Ratio for Kernel Selection of Kernel Methods
Yong Liu, Shizhong Liao. Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2814-2820, 2015

Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand influence function
Yong Liu, Shali Jiang, Shizhong Liao. Proceedings of the 31st International Conference on Machine Learning (ICML), 324-332, 2014

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

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

Randomized Kernel Selection With Spectra of Multilevel Circulant Matrices
Li-Zhong Ding, Shizhong Liao, Yong Liu, Peng Yang, Xin Gao. Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2497-2503, 2018

Granularity Selection for Cross-Validation of SVM
Yong Liu, Shizhong Liao. Information Sciences, 378:475-483, 2017

Learning Entity and Relation Embeddings for Knowledge Resolution
Hailun Lin, Yong Liu*, Weiping Wang, Yinliang Yue, Zheng Lin. Procedia Computer Science, 108:345-354, 2017

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

Kernel Selection with Spectral Perturbation Stability of Kernel Matrix
Yong Liu, Shizhong Liao. Science China Information Sciences 57(11):1-10, 2014

Error Analysis for Vector-Valued Regularized Least-Squares Algorithm
Yong Liu, Shizhong Liao. Proceedings on the International Conference on Artificial Intelligence (ICAI), 2014

Eigenvalues Perturbation of Integral Operator for Kernel Selection
Yong Liu, Shali Jiang, Shizhong Liao. Proceedings of the 22nd ACM international Conference on Information and Knowledge Management (CIKM), 2189-2198, 2013

An Explicit Description of the Extended Gaussian Kernel
Yong Liu, Shizhong Liao. Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, 88-99, 2012 (Best Paper)

Learning Kernels with Upper Bounds of Leave-One-Out error
Yong Liu, Shizhong Liao, Yuexian Hou. Proceedings of the 20th ACM international Conference on Information and Knowledge Management (CIKM), 2205-2208, 2011

An Error Bound for Eigenvalues of Graph Laplacian with Bounded Kernel Function
Yong Liu, Shizhong Liao. Proceedings of Seventh International Conference on Computational Intelligence and Security (CIS), 435-440, 2011

Kernel Construction via Generalized Eigenvector Decomposition
Yong Liu, Shizhong Liao. Foundations of Intelligent Systems, 191-200, 2011

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

基于积分算子空间显式描述的框架核选择方法
刘勇, 廖士中. 中国科学:信息科学, 46(2):165-178, 2016

基于支持向量机泛化误差界的多核学习方法
刘勇, 廖士中. 武汉大学学报(理学版), 58(2), 2012