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ORCIDWeiwei Liu 0003
Person information
- unicode name: 刘威威
- affiliation: Wuhan University, School of Computer Science, Wuhan, China
- affiliation: University of New South Wales, School of Computer Science and Engineering, Sydney, NSW, Australia
- affiliation (PhD 2017): University of Technology Sydney, Ultimo, NSW, Australia
Other persons with the same name
- Weiwei Liu (aka: Wei-Wei Liu) — disambiguation page
- Weiwei Liu 0001 (aka: Wei-Wei Liu 0001) — Chinese People's Liberation Army, 62315 Unit, Beijing, China (and 2 more)
- Weiwei Liu 0002
![[0000-0001-7353-9136]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-7353-9136")
— Nanjing University of Science and Technology, School of Automation, China - Weiwei Liu 0004 — Shandong University, Department of Computer Science and Technology, Jinan, China
- Weiwei Liu 0005 — North China University of Water Resources and Electric Power, School of Mathematics and Statistics, Zhengzhou, China (and 1 more)
- Weiwei Liu 0006 — Harbin Engineering University, School of Economics and Management, China (and 1 more)
- Weiwei Liu 0008 — City University of Hong Kong, Department of Computer Science, Kowloon, Hong Kong
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Journal Articles
- 2023
[j15]Xiaobo Shen, Yew-Soon Ong, Zheng Mao, Shirui Pan, Weiwei Liu, Yuhui Zheng:
Compact network embedding for fast node classification. Pattern Recognit. 136: 109236 (2023)- [j14]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Yang Yang, Philip S. Yu:
Signed Network Representation by Preserving Multi-Order Signed Proximity. IEEE Trans. Knowl. Data Eng. 35(3): 3087-3100 (2023) - [j13]Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu:
Task Variance Regularized Multi-Task Learning. IEEE Trans. Knowl. Data Eng. 35(8): 8615-8629 (2023) - 2022
- [j12]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu:
Signed network representation with novel node proximity evaluation. Neural Networks 148: 142-154 (2022) - [j11]Weiwei Liu, Haobo Wang, Xiaobo Shen, Ivor W. Tsang:
The Emerging Trends of Multi-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7955-7974 (2022) - 2021
- [j10]Chuang Liu, Jia Wu, Weiwei Liu, Wenbin Hu:
Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information. Neural Networks 142: 20-33 (2021) - 2020
- [j9]Zhao Li, Haobo Wang, Donghui Ding, Shichang Hu, Zhen Zhang, Weiwei Liu, Jianliang Gao, Zhiqiang Zhang, Ji Zhang:
Deep Interest-Shifting Network with Meta-Embeddings for Fresh Item Recommendation. Complex. 2020: 8828087:1-8828087:13 (2020) - [j8]Weiwei Liu, Xiaobo Shen, Yew-Soon Ong, Ivor W. Tsang, Chen Gong, Vladimir Pavlovic:
Guest Editorial Special Issue on Structured Multi-Output Learning: Modeling, Algorithm, Theory, and Applications. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2236-2239 (2020) - 2019
- [j7]Weiwei Liu, Donna Xu, Ivor W. Tsang, Wenjie Zhang:
Metric Learning for Multi-Output Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 41(2): 408-422 (2019) - [j6]Weiwei Liu, Xiaobo Shen, Bo Du, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin:
Hyperspectral Imagery Classification via Stochastic HHSVMs. IEEE Trans. Image Process. 28(2): 577-588 (2019) - 2018
- [j5]Xiaobo Shen, Fumin Shen, Li Liu, Yunhao Yuan, Weiwei Liu, Quan-Sen Sun:
Multiview Discrete Hashing for Scalable Multimedia Search. ACM Trans. Intell. Syst. Technol. 9(5): 53:1-53:21 (2018) - [j4]Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong:
Multilabel Prediction via Cross-View Search. IEEE Trans. Neural Networks Learn. Syst. 29(9): 4324-4338 (2018) - 2017
- [j3]Weiwei Liu, Ivor W. Tsang:
Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions. J. Mach. Learn. Res. 18: 81:1-81:36 (2017) - [j2]Weiwei Liu, Ivor W. Tsang, Klaus-Robert Müller:
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. J. Mach. Learn. Res. 18: 94:1-94:38 (2017) - 2015
- [j1]Weiwei Liu, Zhi-Hong Deng, Longbing Cao, Xiaoran Xu, He Liu, Xiuwen Gong:
Mining Top K Spread Sources for a Specific Topic and a Given Node. IEEE Trans. Cybern. 45(11): 2472-2483 (2015)
Conference and Workshop Papers
- 2024
- [c34]Zekai Wang, Zhengyu Zhou, Weiwei Liu:
DRF: Improving Certified Robustness via Distributional Robustness Framework. AAAI 2024: 15752-15760 - 2023
- [c33]Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan:
Better Diffusion Models Further Improve Adversarial Training. ICML 2023: 36246-36263 - [c32]Chenglin Yu, Xinsong Ma, Weiwei Liu:
Delving into Noisy Label Detection with Clean Data. ICML 2023: 40290-40305 - [c31]Haobo Wang, Shisong Yang, Gengyu Lyu, Weiwei Liu, Tianlei Hu, Ke Chen, Songhe Feng, Gang Chen:
Deep Partial Multi-Label Learning with Graph Disambiguation. IJCAI 2023: 4308-4316 - 2022
- [c30]Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Pengtao Xie:
MetaWeighting: Learning to Weight Tasks in Multi-Task Learning. ACL (Findings) 2022: 3436-3448 - [c29]Zekai Wang, Weiwei Liu:
Robustness Verification for Contrastive Learning. ICML 2022: 22865-22883 - [c28]Xinsong Ma, Zekai Wang, Weiwei Liu:
On the Tradeoff Between Robustness and Fairness. NeurIPS 2022 - 2021
- [c27]Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu:
BanditMTL: Bandit-based Multi-task Learning for Text Classification. ACL/IJCNLP (1) 2021: 5506-5516 - 2020
- [c26]Zhenyu Qiu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Xiaohua Jia:
Temporal Network Embedding with High-Order Nonlinear Information. AAAI 2020: 5436-5443 - [c25]Haobo Wang, Chen Chen, Weiwei Liu, Ke Chen, Tianlei Hu, Gang Chen:
Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification. AAAI 2020: 6178-6185 - [c24]Yuren Mao, Shuang Yun, Weiwei Liu, Bo Du:
Tchebycheff Procedure for Multi-task Text Classification. ACL 2020: 4217-4226 - [c23]Yuren Mao, Weiwei Liu, Xuemin Lin:
Adaptive Adversarial Multi-task Representation Learning. ICML 2020: 6724-6733 - [c22]Xinjian Huang, Bo Du, Weiwei Liu:
Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization. IJCAI 2020: 637-644 - [c21]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu:
Opinion Maximization in Social Trust Networks. IJCAI 2020: 1251-1257 - [c20]Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen:
Collaboration Based Multi-Label Propagation for Fraud Detection. IJCAI 2020: 2477-2483 - [c19]Haobo Wang, Weiwei Liu, Yang Zhao, Tianlei Hu, Ke Chen, Gang Chen:
Learning From Multi-Dimensional Partial Labels. IJCAI 2020: 2943-2949 - [c18]Haobo Wang, Yuzhou Qiang, Chen Chen, Weiwei Liu, Tianlei Hu, Zhao Li, Gang Chen:
Online Partial Label Learning. ECML/PKDD (2) 2020: 455-470 - 2019
- [c17]Chen Chen, Haobo Wang, Weiwei Liu, Xingyuan Zhao, Tianlei Hu, Gang Chen:
Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification. AAAI 2019: 3304-3311 - [c16]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Jian Yang:
Social Trust Network Embedding. ICDM 2019: 678-687 - [c15]Weiwei Liu, Xiaobo Shen:
Sparse Extreme Multi-label Learning with Oracle Property. ICML 2019: 4032-4041 - [c14]Haobo Wang, Weiwei Liu, Yang Zhao, Chen Zhang, Tianlei Hu, Gang Chen:
Discriminative and Correlative Partial Multi-Label Learning. IJCAI 2019: 3691-3697 - [c13]Weiwei Liu:
Copula Multi-label Learning. NeurIPS 2019: 6334-6343 - 2018
- [c12]Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin:
Doubly Approximate Nearest Neighbor Classification. AAAI 2018: 3683-3690 - [c11]Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong:
Compact Multi-Label Learning. AAAI 2018: 4066-4073 - [c10]Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang:
Deep Discrete Prototype Multilabel Learning. IJCAI 2018: 2675-2681 - [c9]Jing Wang, Feng Tian, Weiwei Liu, Xiao Wang, Wenjie Zhang, Kenji Yamanishi:
Ranking Preserving Nonnegative Matrix Factorization. IJCAI 2018: 2776-2782 - [c8]Xiaobo Shen, Shirui Pan, Weiwei Liu, Yew-Soon Ong, Quan-Sen Sun:
Discrete Network Embedding. IJCAI 2018: 3549-3555 - 2017
- [c7]Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun:
Compressed K-Means for Large-Scale Clustering. AAAI 2017: 2527-2533 - [c6]Jing Chai, Weiwei Liu, Ivor W. Tsang, Xiao-Bo Shen:
Compact Multiple-Instance Learning. CIKM 2017: 2007-2010 - [c5]Weiwei Liu, Xiao-Bo Shen, Ivor W. Tsang:
Sparse Embedded k-Means Clustering. NIPS 2017: 3319-3327 - 2016
- [c4]Weiwei Liu, Ivor W. Tsang:
Sparse Perceptron Decision Tree for Millions of Dimensions. AAAI 2016: 1881-1887 - 2015
- [c3]Weiwei Liu, Zhi-Hong Deng, Xiuwen Gong, Frank Jiang, Ivor W. Tsang:
Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network. AAAI 2015: 210-216 - [c2]Weiwei Liu, Ivor W. Tsang:
Large Margin Metric Learning for Multi-Label Prediction. AAAI 2015: 2800-2806 - [c1]Weiwei Liu, Ivor W. Tsang:
On the Optimality of Classifier Chain for Multi-label Classification. NIPS 2015: 712-720
Informal and Other Publications
- 2023
- [i6]Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan:
Better Diffusion Models Further Improve Adversarial Training. CoRR abs/2302.04638 (2023) - [i5]Haobo Wang, Shisong Yang, Gengyu Lyu, Weiwei Liu, Tianlei Hu, Ke Chen, Songhe Feng, Gang Chen:
Deep Partial Multi-Label Learning with Graph Disambiguation. CoRR abs/2305.05882 (2023) - 2022
- [i4]Xiaowen Wei, Weiwei Liu, Yibing Zhan, Bo Du, Wenbin Hu:
CLNode: Curriculum Learning for Node Classification. CoRR abs/2206.07258 (2022) - 2020
- [i3]Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu:
Opinion Maximization in Social Trust Networks. CoRR abs/2006.10961 (2020) - [i2]Xinjian Huang, Weiwei Liu, Bo Du:
Matrix Completion with Noise via Leveraged Sampling. CoRR abs/2011.05885 (2020) - [i1]Weiwei Liu, Xiaobo Shen, Haobo Wang, Ivor W. Tsang:
The Emerging Trends of Multi-Label Learning. CoRR abs/2011.11197 (2020)
Coauthor Index
aka: Xiao-Bo Shen
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