海报
工作经历
中国人民大学高瓴人工智能学院，长聘副教授，2024年8月至今
中国人民大学高瓴人工智能学院，准聘副教授，2021年7月-2024年8月
中国人民大学高瓴人工智能学院，准聘助理教授， 2020年8月-2021年7月
中国科学院信息工程研究所，副研究员，2018年10月-2020年7月
中国科学院信息工程研究所，助理研究员，2016年7月-2018年10月
研究方向
总方向为机器学习算法与理论，具体聚焦以下几个方面：
--1）大模型学习算法与理论
--2）Agent：大模型推理、Agent应用
--3）推荐检索：基于大模型推荐算法研究
学生要求
努力且有激情的学生
毕业学生：
李健（2020毕业），北京师范大学 副教授；
殷荣（2020毕业），中科院信工所 副研究员；
李少杰 （2024毕业，博士），新加坡国立博士后；
胡啸林 （2025毕业，博士），厦门大学讲师；
胡羽蓝（2025毕业，博士），阿里；
杨杰超（2025毕业，博士），移动研究院；
杨智睿（2025毕业，硕士），快手
教授课程
神经网络与深度学习，研究生课程
海量数据挖掘，研究生课程
深度学习导论，本科课程
科研项目
面向高效计算与推理的大模型新型范式设计与优化，150万，北京市交叉融通重点项目，2025-2028，项目负责人
大模型记忆和生成机理合作研究，105万，国家重点研发计划，2025.1-2027.12，任务负责人
基于分布式强化学习的稠密奖励组相对策略优化研究，30万，腾讯AI Lab犀牛鸟专项研究计划，2025.7-2026.6 负责人
大语言模型上下文学习的数学机理分析和设计， 50万， 自然科学基金面上项目， 2025.1-2028.12 负责人
Prompt中引导示例自动构建与选择 75万，华为联合项目， 2024.9--2025.9， 负责人
基于ReAct Agent与检索知识增强的大模型营销场景下的对话应用研究， 30万， 阿里妈妈， 2024.8--2025.8 负责人
端侧大模型的个性化高效微调关键技术研究， 20万， 小米，2024.7--2025.7 负责人
电网企业专利价值量化评估关键技术研究 80万，国家电网， 2023-2025， 课题负责人，
面向多类型多模态图数据的通用大模型技术与药物发现应用研究， 北京市科技计划（中央引导地方专项），2023.9-2025.08 子课题负责人
面向多场景的大规模异配图表征，58.9万，华为，2023.3-2024.3，负责人
2022年联通研究院面向深度模型的自动机器学习研究技术服务，80万，联通，2022.12-2023.12，负责人
非凸随机优化理论与算法研究， 12万，CCF-华为胡杨林基金，2022.10--2023.9，负责人
基于图神经网络的反事实欺诈检测算法研究 30万，腾讯微信支付犀牛鸟专项， 2022.5-2023.5，负责人
大规模半监督核学习的模型选择理论与算法研究 20万，北京市自然科学基金面上项目，2022.1-2024.12， 负责人
大规模实时用户表征，40万，华为，2022.1-2023.1，负责人
面向联通应用场景的自动机器学习，20万，联通，2021.11-2022.3，负责人
大规模深度核学习的理论与算法研究 59万，国家自然科学基金面上项目，2021.1-2024.12，负责人
大规模核方法积分算子谱分析的模型选择方法，国家自然科学基金青年项目，24万，2018.1-2020.12，负责人
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
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
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
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 (获得优秀)，负责人
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
学术论文
2025
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning
Guikun Chen, Xu Zhang, Xiaolin Hu,Yong Liu,Yi Yang,Wenguan Wang
Nature Communications
Revisiting Chain-of-Thought Prompting: Zero-shot Can Be Stronger than Few-shot
Xiang Cheng, Chengyan Pan, Minjun Zhao, Deyang Li, Fangchao Liu, Xinyu Zhang, Xiao Zhang, Yong Liu
In ENNLP 2025
Reward Mixology: Crafting Hybrid Signals for Reinforcement Learning Driven In-Context Learning
Changshuo Zhang, Ang Gao, Xiao Zhang, Yong Liu, Deyang Li, Fangchao Liu, Xinyu Zhang
In ENNLP 2025
SPPD: Self-training with Process Preference Learning Using Dynamic Value Margin
Hao Yi, Qingyang Li, Yulan Hu, Fuzheng Zhang, Di ZHANG, Yong Liu
In ENNLP 2025
Exploring the Limitations of Mamba in COPY and CoT Reasoning
Ruifeng Ren, Zhicong Li, Yong Liu
In ENNLP 2025
Revisiting Weak-to-Strong Generalization in Theory and Practice: Reverse KL vs. Forward KL
Wei Yao, Wenkai Yang, Ziqiao Wang, Yankai Lin, Yong Liu
In ACL 2025
Towards Reward Fairness in RLHF: From a Resource Allocation Perspective
Sheng Ouyang, Yulan Hu, Ge Chen, Qingyang Li, Fuzheng Zhang, Yong Liu
In ACL 2025
The Tug of War Within: Mitigating the Fairness-Privacy Conflicts in Large Language Models
Chen Qian, Dongrui Liu, Jie Zhang, Yong Liu, Jing Shao
In ACL 2025
Do not Abstain! Identify and Solve the Uncertainty
Jingyu Liu, JingquanPeng, xiaopeng Wu, Xubin Li, Tiezheng Ge, Bo Zheng, Yong Liu
In ACL 2025
Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and Optimization
Xinhao Yao ,Hongjin Qian,Xiaolin Hu,Gengze Xu,Wei Liu,Jian Luan,Bin Wang,Yong Liu
In IJCAI 2025
Towards Improved Risk Bounds for Transductive Learning
Bowei Zhu, Shaojie Li, Yong Liu
In IJCAI 2025
Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning
Zeyu Gan, Yun Liao, Yong Liu
In ICML 2025
Understanding Model Ensemble in Transferable Adversarial Attack
Wei Yao, Zeliang Zhang, Huayi Tang, Yong Liu
In ICML 2025
Towards Auto-Regressive Next-Token Prediction: In-context Learning Emerges from Generalization
Zixuan Gong, Xiaolin Hu, Huayi Tang, Yong Liu
In ICLR 2025
Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspective
Zeyu Gan, Yong Liu
In ICLR 2025
ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
Pengwei Tang, Xiaolin Hu, Yong Liu
In ICLR 2025
Super(ficial)-alignment: Strong Models May Deceive Weak Models in Weak-to-Strong Generalization
Wenkai Yang, Shiqi Shen, Guangyao Shen, Wei Yao, Yong Liu, Gong Zhi, Yankai Lin, Ji-Rong Wen
In ICLR 2025
REEF: Representation Encoding Fingerprints for Large Language Models
Jie Zhang, Dongrui Liu, Chen Qian, Linfeng Zhang, Yong Liu, Yu Qiao, Jing Shao
In ICLR 2025
2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications
Huayi Tang, Yong Liu
JMLR
PATNAS: A Path-Based Training-Free Neural Architecture Search
Jiechao Yang, Yong Liu*, Wei Wang, Haoran Wu, Zhiyuan Chen, Xibo Ma*
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI)
Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective
Xinhao Yao , Xiaolin Hu , Shenzhi Yang , Yong Liu∗
In NeurIPS 2024
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Towards Understanding How Transformers Learn In-context Through a Representation Learning Lens
Ruifeng Ren, Yong Liu*
In NeurIPS 2024
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Concentration and Moment Inequalities for General Functions of Independent Random Variables with Heavy Tails
Shaojie Li, Yong Liu*
In JMLR
Hybrid federated learning with brain-region attention network for multi-center Alzheimer's disease detection
Baiying Lei, Yu Liang, Jiayi Xie, You Wu, Enmin Liang, Yong Liu, Peng Yang, Tianfu Wang, Chuan-Ming Liu, Jichen Du, Xiaohua Xiao, Shuqiang Wang
Pattern Recognition
Unbiased and augmentation-free self-supervised graph representation learning
Ruyue Liu, Rong Yin, Yong Liu, Weiping Wang
Pattern Recognition
A survey on model compression for large language models
Xunyu Zhu, Jian Li, Yong Liu*, Can Ma, Weiping Wang
In TACL (CCF A)
Reimagining Graph Classification from a Prototype View with Optimal Transport: Algorithm and Theorem
Chen Qian, Huayi Tang, Hong Liang, Yong Liu*
In KDD
Towards Tracing Trustworthiness Dynamics: Revisiting Pre-training Period of Large Language Models
Chen Qian, Jie Zhang, Wei Yao, Dongrui Liu, Zhenfei Yin, Yu Qiao, Yong Liu*, Jing Shao*
In ACL
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ETAS: Zero-Shot Transformer Architecture Search via Network Trainability and Expressivity
Jiechao Yang, Yong Liu*
In ACL
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Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
Shaojie Li, Bowei Zhu, Yong Liu*
In ICML 2024
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Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
Shaojie Li, Yong Liu
In ICML 2024
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Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu, Huayi Tang, Yong Liu*
In ICML 2024
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IdmMAE: Importance-Inspired Dynamic Masking for Graph Autoencoders
Ge Chen, Yulan Hu, Sheng Ouyang, Zhirui Yang, Yong Liu, Cuicui Luo
In SIGIR
Advancing Latent Representation Ranking for Masked Graph Autoencoder
Yulan Hu, Ge Chen, Sheng Ouyang, Zhirui Yang, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Shangquan Wu, Zhao Cao, Yong Liu
In DASFAA 2024
Towards Sharper Risk Bounds for Minimax Problems
Bowei Zhu, Shaojie Li, Yong Liu
In IJCAI
On the Consistency and Large-Scale Extension of Multiple Kernel Clustering
Weixuan Liang, Chang Tang, Xinwang Liu, Yong Liu*, Jiyuan Liu, En Zhu, Kunlun He
IEEE TPAMI
High-dimensional analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm
Jian Li, Yong Liu*, Weiping Wang
In AAAI
ASWT-SGNN: Adaptive Spectral Wavelet Transform-based Self-Supervised Graph Neural Network
Ruyue Liu, Rong Yin, Yong Liu,Weiping Wang
In AAAI
WaveNet: Tackling Non-Stationary Graph Signals via Graph Spectral Wavelets
Zhirui Yang, Yulan Hu, Sheng Ouyang, Jingyu Liu,Shuqiang Wang, Xibo Ma, Wenhan Wang, Hanjing Su, Yong Liu*
In AAAI
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FedNS: A Fast Sketching Newton-Type Algorithm for Federated Learning
Jian Li , Yong Liu*, Wei Wang , Haoran Wu, Weiping Wang
In AAAI
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GFMAE: Self-Supervised GNN-Free Masked AutoEncoders
Yulan Hu, Sheng Ouyang, Zhirui Yang, Yi Zhao, Junchen Wan, Fuzheng Zhang, Zhongyuan Wang, Yong Liu
ICASSP
2023
Theoretical analysis of divide-and-conquer ERM: From the perspective of multi-view
Yun Liao, Yong Liu*, Shizhong Liao, Qinhua Hu, Jianwu Dang
Information Fusion
Optimal Rates for Agnostic Distributed Learning
Jian Li, Yong Liu*, Weiping Wang
IEEE Transactions on Information Theory
Optimal Convergence for Agnostic Kernel Learning With Random Feature
Jian Li, Yong Liu*, Weiping Wang
IEEE Transactions on Neural Networks and Learning Systems
In-context Learning with Transformer Is Really Equivalent to a Contrastive Learning Pattern
Ruifeng Ren, Yong Liu
Arxiv
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Morphological Feature Visualization of Alzheimer's Disease via Multidirectional Perception GAN
Wen Yu, Baiying Lei, Shuqiang Wang, Yong Liu, Zhiguang Feng, Yong Hu, Yanyan Shen, Michael K. Ng
IEEE Transactions on Neural Networks and Learning Systems
Semantic-Aware Dehazing Network With Adaptive Feature Fusion
Shengdong Zhang, Wenqi Ren, Xin Tan, Zhi-Jie Wang, Yong Liu, Jingang Zhang, Xiaoqin Zhang, Xiaochun Cao
IEEE Transactions on Cybernetics
Improving Differentiable Architecture Search via Self-Distillation
Xunyu Zhu, Jian Li, Yong Liu, Weiping Wang
Neural Networks
Towards practical differential privacy in data analysis: Understanding the effect of epsilon on utility in private ERM
Yuzhe Li, Yong Liu, Bo Li, Weiping Wang, Nan Liu
Computers & Security
High Probability Analysis for Non-Convex Stochastic Optimization with Clipping
Shaojie Li, Yong Liu*
In ECAI 2023
Optimal Convergence Rates for Distributed Nystrom Approximation
Jian Li, Yong Liu*, Weiping Wang
Journal of Machine Learning Research
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Towards Understanding the Generalization of Graph Neural Networks
Huayi Tang and Yong Liu*
In ICML 2023
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Distribution-dependent McDiarmid-type Inequalities for Functions of Unbounded Interaction
Shaojie Li, Yong Liu*
In ICML 2023
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Optimal Convergence Rates for Agnostic Nystrom Kernel Learning
Jian Li, Yong Liu*, Weiping Wang
In ICML 2023
下载： 论文文档
Consistency of Multiple Kernel Clustering
Weixuan Liang, Xinwang Liu, Yong Liu, Chuan Ma, Yunping Zhao, Zhe Liu, En Zhu
In ICML 2013
Fair Scratch Tickets: Finding Fair Sparse Networks without Weight Training
Penwei Tang, Wei Yao, Zhicong Li, Yong Liu*
In CVPR 2023
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HOTNAS: Hierarchical Optimal Transport for Neural Architecture Search
Jiechao Yang, Yong Liu*
In CVPR 2023
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Learning Rates for Nonconvex Pairwise Learning
Shaojie Li, Yong Liu*
IEEE Transactions on Pattern Analysis and Machine Intelligence (CCF A)
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Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses
Xiaolin Hu, Shaojie Li, Yong Liu*
In ICLR
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Semi-supervised Vector-valued Learning: Improved Bounds and Algorithms
Jian Li, Yong Liu*, Weiping Wang
Pattern Recognition
Understanding the Generalization Performance of Spectral Clustering Algorithms
Shaojie Li, Sheng Ouyang, Yong Liu*
In AAAI 2023 (CCF A)
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2022
Scalable Kernel k-Means with Randomized Sketching: From Theory to Algorithm
Rong Yin, Yong Liu*, Xueyan Wang, Weiping Wang, Dan Meng
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022 (CCF A)
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Non-IID Federated Learning with Sharper Risk Bound
Bojian Wei, Jian Li, Yong Liu and Weiping Wang
IEEE Transactions on Neural Networks and Learning Systems (SCI 一区)
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Convolutional Spectral Kernel Learning with Generalization Guarantees
Jian Li, Yong Liu*, and Weiping Wang
Artificial Intelligence （CCF A）
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Fine-Grained Analysis of Stability and Generalization for Modern Meta Learning Algorithms
Jiechao Guan, Yong Liu and Zhiwu Lu
In NeurIPS 2022 （CCF A）
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Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel
Weixuan Liang, Xinwang Liu，Yong Liu，Sihang zhou, Jun-Jie Huang, Siwei Wang, Jiyuan Liu, Yi Zhang, En Zhu
In NeurIPS 2022 （CCF A）
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Randomized Sketches for Clustering: Fast and Optimal Kernel $k$-Means
Rong Yin, Yong Liu, Weiping Wang and Dan Meng
In NeurIPS 2022 （CCF A）
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Sharper Utility Bounds for Differentially Private Models: Smooth and Non-smooth
康艺霖，刘勇*，李健，王伟平
In CIKM 2022 (CCF B)
基于稳定性分析的非凸在线点对学习的遗憾界
郎璇聪，李春生，刘勇，王梅
计算机研究与发展（第九界中国数据挖掘会议最佳论文）
Non-IID Distributed Learning with Optimal Mixture Weights
Jian Li, Bojian Wei, Yong Liu, Weiping Wang
In ECML 2022 (CCF B)
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High Probability Guarantees for Nonconvex Stochastic Gradient Descent with Heavy Tails
Shaojie Li, Yong Liu*
In ICML 2022 (CCF A)
下载： 论文文档
Deep Safe Incomplete Multi-view Clustering: Theorem and Algorithm
Huayi Tang and Yong Liu*
In ICML 2022 (CCF A)
Ridgeless Regression with Random Features
Jian Li , Yong Liu*, Yingying Zhang
In IJCAI 2022 (CCF A)
下载： 论文文档
Deep Safe Multi-view Clustering: Reducing the Risk of Clustering Performance Degradation Caused by View Increase
Huayi Tang, Yong Liu*
CVPR 2022 (CCF A)
下载： 论文文档
High Probability Generalization Bounds for Minimax Problems with Fast Rates
Shaojie Li, Yong Liu*
ICLR 2022
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Distributed Randomized Sketching Kernel Learning
Rong Yin, Yong Liu*, Dang Men
AAAI (CCF A)
下载： 论文文档
2021
Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation
Shaogao lv, Junhui Wang, Jiankun Liu, Yong Liu*
In: Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), CCF A, Spotlights (accept rate < 3%))
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Towards Sharper Generalization Bounds for Structured Prediction
Shaojie Li, Yong Liu*
In: Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), CCF A
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Refined Learning Bounds for Kernel and Approximate $k$-Means
Yong Liu
In: Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), CCF A, Spotlights (accept rate < 3%))
下载： 论文文档
Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN
Wen Yu, Baiying Lei, Yong Liu, Zhiguang Feng, Yong Hu, Yanyan Shen, Shuqiang Wang, Michael K. Ng
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021 (SCI 一区) (To Appear)
下载： 论文文档
Operation-level Progressive Differentiable Architecture Search
Xunyu Zhu, Jian Li, Yong Liu*, Weiping Wang
ICDM 2021
下载： 论文文档
Federated Learning for Non-IID Data: From Theory to Algorithm (Best Student Paper)
Bojian Wei, Jian Li, Yong Liu*, Weiping Wang
Proceedings of the 18th Pacific Rim International Conference on Artificial Intelligence (PRICAI)
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General Approximate Cross Validation for Model Selection: Supervised, Semi-supervised and Pairwise Learning
Bowei Zhu, Yong Liu*
Proceedings of The 29th ACM International Conference on Multimedia (ACM MM) (CCF A)
下载： 论文文档
Weighted distributed differential privacy ERM: Convex and non-convex
Yilin Kang, Yong Liu*, Ben Niu, Weiping Wang
Computers & Security (CCF B)
下载： 论文文档
链接： 链接
Distributed Nystrom Kernel Learning with Communications
Rong Yin, Yong Liu, Weiping Wang, Dan Meng
In: Proceedings of the 28th International Conference on Machine Learning (ICML), (CCF A)
下载： 论文文档
Sharper Generalization Bounds for Clustering
Shaojie Li, Yong Liu*
In: Proceedings of the 28th International Conference on Machine Learning (ICML), (CCF A)
下载： 论文文档
Effective Distributed Learning with Random Features: Improved Bounds and Algorithms
Yong Liu, Jiankun Liu, Shuqiang Wang
In: Proceedings of the 9th International Conference on Learning Representations (ICLR)
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2020
Extremely sparse Johnson- Lindenstrauss transform: From Theory to Algorithm
Rong Yin, Yong Liu*, Weiping Wang, Dang Men
In: Proceedings of the 20th IEEE International Conference on Data Mining (ICDM), 2020:1376-1381 (CCF B)
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Sketch Kernel Ridge Regression using Circulant Matrix: Algorithm and Theory.
Rong Yin, Yong Liu*, Weiping Wang, et al
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 31(9): 3512-3524, 2020 (SCI 一区)
下载： 论文文档
Approximate Kernel Selection via Matrix Approximation.
Lizhong Ding, Shizhong Liao, Yong Liu, Li Liu, Fan Zhu, Yazhou Yao, Ling Shao, Xin Gao
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020. (CCF B)
下载： 论文附件
Automated Spectral Kernel Learning.
Jian Li, Yong Liu*, Weiping Wang
In: Proceedings of 34th Conference on Artificial Intelligence (AAAI), 2020: 4618-4625. (CCF A)
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Divide-and-Conquer Learning with Nyström: Optimal Rate and Algorithm
Rong Yin, Yong Liu*, Lijing Lu, Weiping Wang, Dan Meng
Proceedings of 34th Conference on Artificial Intelligence (AAAI), 2020: 6696-6703. (CCF A)
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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 (TPAMI), 2020,42(5):1083-1096. (CCF A)
下载： 论文附件
2019
Kernel Stability for Model Selection in Kernel-based Algorithms.
Yong Liu, Shizhong Liao, Hua Zhang, et al
IEEE Transactions on Cybernetics (TCYB), 2019. Online, DOI: 10.1109/TCYB.2019. 2923824. （SCI一区）
下载： 论文附件
Approximate Kernel Selection with Strong Approximate Consistency.
Lizhong Ding, Yong Liu, Shizhong Liao, Yu Li, Peng Yang, Yijie Pan, Chao Huang, Ling Shao, Xin Gao
In: Proceedings of 33th Conference on Artificial Intelligence (AAAI), 2019: 3462-3469.
下载： 论文附件
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
In: Proceedings of 33th Conference on Artificial Intelligence (AAAI), 2019:3454-3461.
下载： 论文附件
Learning Structural Representations via Dynamic Object Landmarks Discovery for Sketch Recognition and Retrieval.
Hua Zhang, Peng She, Yong Liu, Jianhou Gan, Xiaochun Cao, Hassan Foroosh
IEEE Transactions on Image Processing (TIP), 2019, 28(9):4486-4499. (CCF A)
下载： 论文附件
Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis.
Jian Li, Yong Liu*, Rong Yin, et al
In: Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019:2887-2893. (CCF A)
下载： 论文文档
Multi-Class Learning using Unlabeled Samples: Theory and Algorithm.
Jian Li, Yong Liu*, Rong Yin , Weiping Wang
Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019: 2880-2886. (CCF A))
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Two Generator Game: Learning to Sample via Linear Goodness-of-Fit Test.
Lizhong Ding, Mengyang Yu, Li Liu, Fan Zhu, Yong Liu, Yu Li, Ling Shao
Advances in Neural Information Processing Systems 32 (NeurIPS), 2019:11257-11268. (CCF A)
下载： 论文附件
2018
Randomized Kernel Selection With Spectra of Multilevel Circulant Matrices.
Lizhong Ding, Shizhong Liao, Yong Liu, Peng Yang, Xin Gao
Proceedings of 32rd Conference on Artificial Intelligence (AAAI), 2018: 2910-2917.
Fast Cross-Validation.
Yong Liu, Hailun Lin, Lizhong Ding, et al
In: Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2910-2917, 2018. (CCF A)
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Multi-Class Learning: From Theory to Algorithm.
Jian Li, Yong Liu*, Rong Yin, et al
Advances in Neural Information Processing Systems 31 (NeurIPS), 1593-1602, 2018. (CCF A)
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2017
Granularity selection for cross-validation of SVM.
Yong Liu, Shizhong Liao
Information Sciences, 2017, 475-483. ( CCF B)
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Efficient Kernel Selection via Spectral Analysis.
Jian Li, Yong Liu, Hailun Lin
In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI), 2017: 2124-2130. (CCF A)
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Infinite Kernel Learning: Generalization Bounds and Algorithms.
Yong Liu, Shizhong Liao, Hailun Lin, et al
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017, 2280-2286. (CCF A)
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Generalization Analysis for Ranking Using Integral Operator,
Yong Liu, Shizhong Liao, Linhai Lun, et al
In: Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017: 2273-2279. (CCF A)
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2016
基于积分算子空间显示描述的框架核选择方法
刘勇，廖士中
中国科学: 信息科学, 2016, 46(2), 165–178. (CCF A 中文期刊)
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2015
Eigenvalues ratio for kernel selection of kernel methods
Yong Liu, Shizhong Liao
In: Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015: 2814–2820. (CCF A)
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2014
Preventing Over-Fitting of Cross-Validation with Kernel Stability
Yong Liu, Shizhong Liao
In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML), 2014:290–305. (CCF B)
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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，2014, 51(10):2171-2177. (CCF A 中文期刊)
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Kernel selection with spectral perturbation stability of kernel matrix
Yong Liu, Shizhong Liao
Science China Information Sciences, 2014, 57: 112103(10) (CCF B)
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Efficient Approximation of Cross-validation for Kernel Methods using Bouligand Influence Function
Yong Liu, Shali Jiang, Shizhong Liao
In: Proceedings of The 31st International Conference on Machine Learning (ICML). 2014, 324-332. (CCF A)
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2013
Eigenvalues Perturbation of Integral operator for Kernel Selection
Yong Liu, Shali Jiang, Shizhong Liao
In: Proceedings of the 22nd ACM International Conference on Information and Knowledge management (CIKM), 2013:2189-2198. (CCF B)
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2011
Learning kernels with upper bounds of leave-one-out error
Yong Liu*, Shizhong Liao, Yuexuan-Hou
In: Proceedings of the 20th ACM International Conference on Information and Knowledge management (CIKM), 2011:2205-2208. (CCF B)
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荣誉奖励
2021年 Best Student Paper PRICAI 2021
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
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
社会兼职
AAAI 2021 高级程序委员
IJCAI 2020，IJCAI 2019 高级程序委员
NeurIPS 2020 2021 程序委员
AAAI 2020，程序委员
ICML 2019 2020 2021，程序委员
ICLR 2021，程序委员
联系
邮箱：liuyonggsai@ruc.edu.cn
个人网页：https://iie-liuyong.github.io/