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ORCIDYong Liu 0018
Person information
- affiliation: Renmin University of China, China
- affiliation (former): Chinese Academy of Sciences, Institute of Information Engineering, Beijing, China
- affiliation (PhD 2016): Tianjin University, School of Computer Science and Technology, Tianjin, China
Other persons with the same name
- Yong Liu — disambiguation page
- Yong Liu 0001
![[0000-0003-3156-7002]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-3156-7002")
— Outreach Corporation, Seattle, WA, USA (and 3 more) - Yong Liu 0002 — Chinese Academy of Sciences, Institute of Automation, Brainnetome Center, Beijing, China
- Yong Liu 0003 — Peking University, College of Environmental Science and Engineering, Beijing, China
- Yong Liu 0004 — Nanjing University of Science and Technology, School of Computer Science and Engineering, China
- Yong Liu 0005 — Southwest Jiaotong University, Key Laboratory of Information Coding and Transmission, Chengdu, China
- Yong Liu 0006 — University of Tennessee, Knoxville, TN, USA
- Yong Liu 0007 — Zhejiang University, Institute of Cyber-Systems and Control, State Key Laboratory of Industrial Control Technology, Hangzhou, China (and 1 more)
- Yong Liu 0008 — Wenzhou Medical University, School of Ophthalmology and Optometry, China
- Yong Liu 0009 — Nanyang Technological University, School of Electrical and Electronic Engineering, Singapore
- Yong Liu 0010 — Aalto University School of Business, Department of Information and Service Economy, Aalto, Finland (and 3 more)
- Yong Liu 0011 — Jilin University, School of Mechanical Science and Engineering, Changchun, China
- Yong Liu 0012 — The University of Aizu, Aizu-Wakamatsu, Japan (and 4 more)
- Yong Liu 0013 — New York University, Tandon School of Engineering, Department of Electrical and Computer Engineering, Brooklyn, NY, USA (and 1 more)
- Yong Liu 0014 — Texas A&M University, College Station, USA
- Yong Liu 0015 — Nottingham Trent University, UK
- Yong Liu 0016 — Tianjin University, School of Electrical and Information Engineering, Tianjin, China
- Yong Liu 0017 — National University of Defense Technology, School of Electronic Science, Changsha, China
- Yong Liu 0019 — University of Science and Technology of China, School of Mathematical Sciences, Hefei, China
- Yong Liu 0020 — Nanyang Technological University, Singapore
- Yong Liu 0021 — Beijing Polytechnic, School of Telecommunication Engineering, Beijing, China
- Yong Liu 0022 — Jiangnan University, School of Business, Wuxi, China
- Yong Liu 0023 — Shanghai Jiao Tong University, China (and 3 more)
- Yong Liu 0024 — Indiana University, Department of Computer Science, Bloomington, IN, USA
- Yong Liu 0025 — Northwestern Polytechnical University, College of Automation, Xi'an, China
- Yong Liu 0026 — A*STAR, Artificial Intelligence Initiative, Singapore (and 2 more)
- Yong Liu 0027 — Beijing University of Posts and Telecommunications, School of Information and Communication Engineering, Beijing Key Laboratory of Network System Architecture and Convergence, China
- Yong Liu 0028 — Chongqing Jiaotong University, School of Economics and Management, Chongqing, China
- Yong Liu 0029 — Heilongjiang University, China
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2020 – today
- 2023
[j11]Shengdong Zhang, Wenqi Ren, Xin Tan, Zhi-Jie Wang, Yong Liu, Jingang Zhang, Xiaoqin Zhang, Xiaochun Cao:
Semantic-Aware Dehazing Network With Adaptive Feature Fusion. IEEE Trans. Cybern. 53(1): 454-467 (2023)- [i22]Xunyu Zhu, Jian Li, Yong Liu, Weiping Wang:
Improving Differentiable Architecture Search via Self-Distillation. CoRR abs/2302.05629 (2023) - [i21]Xunyu Zhu, Jian Li, Yong Liu, Weiping Wang:
Operation-level Progressive Differentiable Architecture Search. CoRR abs/2302.05632 (2023) - 2022
- [j10]Jian Li, Yong Liu, Weiping Wang:
Convolutional spectral kernel learning with generalization guarantees. Artif. Intell. 313: 103803 (2022) - [j9]Guangjun Wu, Xiaochun Yun, Yong Wang, Shupeng Wang, Binbin Li, Yong Liu:
A Sketching Approach for Obtaining Real-Time Statistics Over Data Streams in Cloud. IEEE Trans. Cloud Comput. 10(2): 1462-1475 (2022) - [c46]Rong Yin, Yong Liu, Dan Meng:
Distributed Randomized Sketching Kernel Learning. AAAI 2022: 8883-8891 - [c45]Yilin Kang, Yong Liu, Jian Li, Weiping Wang:
Sharper Utility Bounds for Differentially Private Models: Smooth and Non-smooth. CIKM 2022: 951-961 - [c44]Huayi Tang, Yong Liu:
Deep Safe Multi-view Clustering: Reducing the Risk of Clustering Performance Degradation Caused by View Increase. CVPR 2022: 202-211 - [c43]Shaojie Li, Yong Liu:
High Probability Generalization Bounds with Fast Rates for Minimax Problems. ICLR 2022 - [c42]Shaojie Li, Yong Liu:
High Probability Guarantees for Nonconvex Stochastic Gradient Descent with Heavy Tails. ICML 2022: 12931-12963 - [c41]Huayi Tang, Yong Liu:
Deep Safe Incomplete Multi-view Clustering: Theorem and Algorithm. ICML 2022: 21090-21110 - [c40]Jian Li, Yong Liu, Yingying Zhang:
Ridgeless Regression with Random Features. IJCAI 2022: 3208-3214 - [c39]Jian Li, Bojian Wei, Yong Liu, Weiping Wang:
Non-IID Distributed Learning with Optimal Mixture Weights. ECML/PKDD (4) 2022: 539-554 - [i20]Yilin Kang, Yong Liu, Jian Li, Weiping Wang:
Stability and Generalization of Differentially Private Minimax Problems. CoRR abs/2204.04858 (2022) - [i19]Yilin Kang, Yong Liu, Jian Li, Weiping Wang:
Sharper Utility Bounds for Differentially Private Models. CoRR abs/2204.10536 (2022) - [i18]Shaojie Li, Sheng Ouyang, Yong Liu:
Understanding the Generalization Performance of Spectral Clustering Algorithms. CoRR abs/2205.00281 (2022) - [i17]Jian Li, Yong Liu, Yingying Zhang:
Ridgeless Regression with Random Features. CoRR abs/2205.00477 (2022) - [i16]Yuzhe Li, Yong Liu, Bo Li, Weiping Wang, Nan Liu:
Towards Practical Differential Privacy in Data Analysis: Understanding the Effect of Epsilon on Utility in Private ERM. CoRR abs/2206.03488 (2022) - 2021
- [j8]Yilin Kang, Yong Liu, Ben Niu, Weiping Wang:
Weighted distributed differential privacy ERM: Convex and non-convex. Comput. Secur. 106: 102275 (2021) - [j7]Yong Liu, Shizhong Liao, Hua Zhang, Wenqi Ren, Weiping Wang:
Kernel Stability for Model Selection in Kernel-Based Algorithms. IEEE Trans. Cybern. 51(12): 5647-5658 (2021) - [c38]Xunyu Zhu, Jian Li, Yong Liu, Jun Liao, Weiping Wang:
Operation-level Progressive Differentiable Architecture Search. ICDM 2021: 1559-1564 - [c37]Yong Liu, Jiankun Liu, Shuqiang Wang:
Effective Distributed Learning with Random Features: Improved Bounds and Algorithms. ICLR 2021 - [c36]Shaojie Li, Yong Liu:
Sharper Generalization Bounds for Clustering. ICML 2021: 6392-6402 - [c35]Rong Yin, Yong Liu, Weiping Wang, Dan Meng:
Distributed Nyström Kernel Learning with Communications. ICML 2021: 12019-12028 - [c34]Nannan Tian, Yong Liu, Weiping Wang, Dan Meng:
Automatic CNN Compression Based on Hyper-parameter Learning. IJCNN 2021: 1-8 - [c33]Nannan Tian, Yong Liu, Weiping Wang, Dan Meng:
Fast CNN Inference by Adaptive Sparse Matrix Decomposition. IJCNN 2021: 1-8 - [c32]Nannan Tian, Yong Liu, Weiping Wang, Dan Meng:
Energy-saving CNN with Clustering Channel Pruning. IJCNN 2021: 1-8 - [c31]Bowei Zhu, Yong Liu:
General Approximate Cross Validation for Model Selection: Supervised, Semi-supervised and Pairwise Learning. ACM Multimedia 2021: 5281-5289 - [c30]Yong Liu:
Refined Learning Bounds for Kernel and Approximate $k$-Means. NeurIPS 2021: 6142-6154 - [c29]Shaogao Lv, Junhui Wang, Jiankun Liu, Yong Liu:
Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation. NeurIPS 2021: 21467-21479 - [c28]Jiangning Zhang, Chao Xu, Jian Li, Wenzhou Chen, Yabiao Wang, Ying Tai, Shuo Chen, Chengjie Wang, Feiyue Huang, Yong Liu:
Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model. NeurIPS 2021: 26674-26688 - [c27]Shaojie Li, Yong Liu:
Towards Sharper Generalization Bounds for Structured Prediction. NeurIPS 2021: 26844-26857 - [c26]Bojian Wei, Jian Li, Yong Liu, Weiping Wang:
Federated Learning for Non-IID Data: From Theory to Algorithm. PRICAI (1) 2021: 33-48 - [c25]Yuzhe Li, Yong Liu, Bo Li, Weiping Wang, Nan Liu:
Just Keep Your Concerns Private: Guaranteeing Heterogeneous Privacy and Achieving High Availability for ERM Algorithms. TrustCom 2021: 371-378 - [i15]Yilin Kang, Yong Liu, Jian Li, Weiping Wang:
Differential Privacy for Pairwise Learning: Non-convex Analysis. CoRR abs/2105.03033 (2021) - [i14]Shaojie Li, Yong Liu:
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints. CoRR abs/2107.08686 (2021) - [i13]Shaojie Li, Yong Liu:
Learning Rates for Nonconvex Pairwise Learning. CoRR abs/2111.05232 (2021) - 2020
- [j6]Yong Liu, Shizhong Liao, Shali Jiang, Lizhong Ding, Hailun Lin, Weiping Wang:
Fast Cross-Validation for Kernel-Based Algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 42(5): 1083-1096 (2020) - [j5]Rong Yin, Yong Liu, Weiping Wang, Dan Meng:
Sketch Kernel Ridge Regression Using Circulant Matrix: Algorithm and Theory. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3512-3524 (2020) - [j4]Lizhong Ding, Shizhong Liao, Yong Liu, Li Liu, Fan Zhu, Yazhou Yao, Ling Shao, Xin Gao:
Approximate Kernel Selection via Matrix Approximation. IEEE Trans. Neural Networks Learn. Syst. 31(11): 4881-4891 (2020) - [c24]Jian Li, Yong Liu, Weiping Wang:
Automated Spectral Kernel Learning. AAAI 2020: 4618-4625 - [c23]Rong Yin, Yong Liu, Lijing Lu, Weiping Wang, Dan Meng:
Divide-and-Conquer Learning with Nyström: Optimal Rate and Algorithm. AAAI 2020: 6696-6703 - [c22]Lijing Lu, Rong Yin, Yong Liu, Weiping Wang:
Hashing Based Prediction for Large-Scale Kernel Machine. ICCS (2) 2020: 496-509 - [c21]Rong Yin, Yong Liu, Weiping Wang, Dan Meng:
Extremely Sparse Johnson-Lindenstrauss Transform: From Theory to Algorithm. ICDM 2020: 1376-1381 - [i12]Yilin Kang, Yong Liu, Ben Niu, Xinyi Tong, Likun Zhang, Weiping Wang:
Input Perturbation: A New Paradigm between Central and Local Differential Privacy. CoRR abs/2002.08570 (2020) - [i11]Yilin Kang, Yong Liu, Lizhong Ding, Xinwang Liu, Xinyi Tong, Weiping Wang:
Differentially Private ERM Based on Data Perturbation. CoRR abs/2002.08578 (2020) - [i10]Jian Li, Yong Liu, Weiping Wang:
Convolutional Spectral Kernel Learning. CoRR abs/2002.12744 (2020) - [i9]Yong Liu, Lizhong Ding, Weiping Wang:
Theoretical Analysis of Divide-and-Conquer ERM: Beyond Square Loss and RKHS. CoRR abs/2003.03882 (2020) - [i8]Yong Liu, Lizhong Ding, Hua Zhang, Wenqi Ren, Xiao Zhang, Shali Jiang, Xinwang Liu, Weiping Wang:
Nearly Optimal Risk Bounds for Kernel K-Means. CoRR abs/2003.03888 (2020) - [i7]Jian Li, Yong Liu, Jiankun Liu, Weiping Wang:
Neural Architecture Optimization with Graph VAE. CoRR abs/2006.10310 (2020)
2010 – 2019
- 2019
- [j3]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 Trans. Image Process. 28(9): 4486-4499 (2019) - [c20]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. AAAI 2019: 3454-3461 - [c19]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. AAAI 2019: 3462-3469 - [c18]Hailun Lin, Yong Liu, Peng Zhang, Jianwu Wang:
Representation Learning of Taxonomies for Taxonomy Matching. ICCS (1) 2019: 383-397 - [c17]Jian Li, Yong Liu, Rong Yin, Weiping Wang:
Multi-Class Learning using Unlabeled Samples: Theory and Algorithm. IJCAI 2019: 2880-2886 - [c16]Jian Li, Yong Liu, Rong Yin, Weiping Wang:
Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis. IJCAI 2019: 2887-2893 - [c15]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. NeurIPS 2019: 11257-11268 - [i6]Yong Liu, Jian Li, Guangjun Wu, Lizhong Ding, Weiping Wang:
Efficient Cross-Validation for Semi-Supervised Learning. CoRR abs/1902.04768 (2019) - [i5]Jian Li, Yong Liu, Weiping Wang:
Distributed Learning with Random Features. CoRR abs/1906.03155 (2019) - [i4]Jian Li, Yong Liu, Weiping Wang:
Learning Vector-valued Functions with Local Rademacher Complexity. CoRR abs/1909.04883 (2019) - [i3]Jian Li, Yong Liu, Weiping Wang:
Automated Spectral Kernel Learning. CoRR abs/1909.04894 (2019) - [i2]Yilin Kang, Yong Liu, Weiping Wang:
Weighted Distributed Differential Privacy ERM: Convex and Non-convex. CoRR abs/1910.10308 (2019) - 2018
- [c14]Lizhong Ding, Shizhong Liao, Yong Liu, Peng Yang, Xin Gao:
Randomized Kernel Selection With Spectra of Multilevel Circulant Matrices. AAAI 2018: 2910-2917 - [c13]Yong Liu, Hailun Lin, Lizhong Ding, Weiping Wang, Shizhong Liao:
Fast Cross-Validation. IJCAI 2018: 2497-2503 - [c12]Jian Li, Yong Liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang:
Multi-Class Learning: From Theory to Algorithm. NeurIPS 2018: 1593-1602 - [i1]Yong Liu, Jian Li, Weiping Wang:
Max-Diversity Distributed Learning: Theory and Algorithms. CoRR abs/1812.07738 (2018) - 2017
- [j2]Yong Liu, Shizhong Liao:
Granularity selection for cross-validation of SVM. Inf. Sci. 378: 475-483 (2017) - [c11]Yong Liu, Shizhong Liao, Hailun Lin, Yinliang Yue, Weiping Wang:
Generalization Analysis for Ranking Using Integral Operator. AAAI 2017: 2273-2279 - [c10]Yong Liu, Shizhong Liao, Hailun Lin, Yinliang Yue, Weiping Wang:
Infinite Kernel Learning: Generalization Bounds and Algorithms. AAAI 2017: 2280-2286 - [c9]Hailun Lin, Yong Liu, Weiping Wang, Yinliang Yue, Zheng Lin:
Learning Entity and Relation Embeddings for Knowledge Resolution. ICCS 2017: 345-354 - [c8]Jian Li, Yong Liu, Hailun Lin, Yinliang Yue, Weiping Wang:
Efficient Kernel Selection via Spectral Analysis. IJCAI 2017: 2124-2130 - 2015
- [c7]Yong Liu, Shizhong Liao:
Eigenvalues Ratio for Kernel Selection of Kernel Methods. AAAI 2015: 2814-2820 - 2014
- [j1]Yong Liu, Shizhong Liao:
Kernel selection with spectral perturbation stability of kernel matrix. Sci. China Inf. Sci. 57(11): 1-10 (2014) - [c6]Yong Liu, Shali Jiang, Shizhong Liao:
Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function. ICML 2014: 324-332 - [c5]Yong Liu, Shizhong Liao:
Preventing Over-Fitting of Cross-Validation with Kernel Stability. ECML/PKDD (2) 2014: 290-305 - 2013
- [c4]Yong Liu, Shali Jiang, Shizhong Liao:
Eigenvalues perturbation of integral operator for kernel selection. CIKM 2013: 2189-2198 - 2012
- [c3]Yong Liu, Shizhong Liao:
An Explicit Description of the Extended Gaussian Kernel. PAKDD Workshops 2012: 88-99 - 2011
- [c2]Yong Liu, Shizhong Liao, Yuexian Hou:
Learning kernels with upper bounds of leave-one-out error. CIKM 2011: 2205-2208 - [c1]Yong Liu, Shizhong Liao:
An Error Bound for Eigenvalues of Graph Laplacian with Bounded Kernel Function. CIS 2011: 436-440
Coauthor Index
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