Weiwei Liu

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 53

Top Topics

Text Classification

Negative Matrix Factorization

Approximate Nearest Neighbor

Multiple Classes

Top Venues

Publications

Haobo Wang, Cheng Peng, Hede Dong, Lei Feng, Weiwei Liu, Tianlei Hu, Ke Chen, Gang Chen
On the Value of Head Labels in Multi-Label Text Classification. ACM Trans. Knowl. Discov. Data 18 (5) (2024)
Zekai Wang, Zhengyu Zhou, Weiwei Liu
DRF: Improving Certified Robustness via Distributional Robustness Framework. AAAI (2024)
Xinjian Huang, Weiwei Liu, Bo Du, Dacheng Tao
Leveraged Matrix Completion With Noise. IEEE Trans. Cybern. 54 (8) (2024)
Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan
Better Diffusion Models Further Improve Adversarial Training. ICML (2023)
Chenglin Yu, Xinsong Ma, Weiwei Liu
Delving into Noisy Label Detection with Clean Data. ICML (2023)
Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu
Task Variance Regularized Multi-Task Learning. IEEE Trans. Knowl. Data Eng. 35 (8) (2023)
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)
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) (2023)
Xiaobo Shen, Yew-Soon Ong, Zheng Mao, Shirui Pan, Weiwei Liu, Yuhui Zheng
Compact network embedding for fast node classification. Pattern Recognit. 136 (2023)
Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan
Better Diffusion Models Further Improve Adversarial Training. CoRR (2023)
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 (2023)
Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu
Signed network representation with novel node proximity evaluation. Neural Networks 148 (2022)
Zekai Wang, Weiwei Liu
Robustness Verification for Contrastive Learning. ICML (2022)
Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Pengtao Xie
MetaWeighting: Learning to Weight Tasks in Multi-Task Learning. ACL (Findings) (2022)
Xiaowen Wei, Weiwei Liu, Yibing Zhan, Bo Du, Wenbin Hu
CLNode: Curriculum Learning for Node Classification. CoRR (2022)
Xinsong Ma, Zekai Wang, Weiwei Liu
On the Tradeoff Between Robustness and Fairness. NeurIPS (2022)
Weiwei Liu, Haobo Wang, Xiaobo Shen, Ivor W. Tsang
The Emerging Trends of Multi-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (11) (2022)
Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu
BanditMTL: Bandit-based Multi-task Learning for Text Classification. ACL/IJCNLP (1) (2021)
Chuang Liu, Jia Wu, Weiwei Liu, Wenbin Hu
Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information. Neural Networks 142 (2021)
Haobo Wang, Yuzhou Qiang, Chen Chen, Weiwei Liu, Tianlei Hu, Zhao Li, Gang Chen
Online Partial Label Learning. ECML/PKDD (2) (2020)
Yuren Mao, Weiwei Liu, Xuemin Lin
Adaptive Adversarial Multi-task Representation Learning. ICML (2020)
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 (2020)
Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu
Opinion Maximization in Social Trust Networks. IJCAI (2020)
Xinjian Huang, Bo Du, Weiwei Liu
Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization. IJCAI (2020)
Haobo Wang, Chen Chen, Weiwei Liu, Ke Chen, Tianlei Hu, Gang Chen
Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification. AAAI (2020)
Xinjian Huang, Weiwei Liu, Bo Du
Matrix Completion with Noise via Leveraged Sampling. CoRR (2020)
Weiwei Liu, Xiaobo Shen, Haobo Wang, Ivor W. Tsang
The Emerging Trends of Multi-Label Learning. CoRR (2020)
Haobo Wang, Weiwei Liu, Yang Zhao, Tianlei Hu, Ke Chen, Gang Chen
Learning From Multi-Dimensional Partial Labels. IJCAI (2020)
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) (2020)
Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu
Opinion Maximization in Social Trust Networks. CoRR (2020)
Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen
Collaboration Based Multi-Label Propagation for Fraud Detection. IJCAI (2020)
Zhenyu Qiu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Xiaohua Jia
Temporal Network Embedding with High-Order Nonlinear Information. AAAI (2020)
Yuren Mao, Shuang Yun, Weiwei Liu, Bo Du
Tchebycheff Procedure for Multi-task Text Classification. ACL (2020)
Weiwei Liu, Donna Xu, Ivor W. Tsang, Wenjie Zhang
Metric Learning for Multi-Output Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 41 (2) (2019)
Weiwei Liu, Xiaobo Shen
Sparse Extreme Multi-label Learning with Oracle Property. ICML (2019)
Weiwei Liu
Copula Multi-label Learning. NeurIPS (2019)
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)
Haobo Wang, Weiwei Liu, Yang Zhao, Chen Zhang, Tianlei Hu, Gang Chen
Discriminative and Correlative Partial Multi-Label Learning. IJCAI (2019)
Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Jian Yang
Social Trust Network Embedding. ICDM (2019)
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) (2019)
Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong
Compact Multi-Label Learning. AAAI (2018)
Jing Wang, Feng Tian, Weiwei Liu, Xiao Wang, Wenjie Zhang, Kenji Yamanishi
Ranking Preserving Nonnegative Matrix Factorization. IJCAI (2018)
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) (2018)
Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin
Doubly Approximate Nearest Neighbor Classification. AAAI (2018)
Xiaobo Shen, Shirui Pan, Weiwei Liu, Yew-Soon Ong, Quan-Sen Sun
Discrete Network Embedding. IJCAI (2018)
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) (2018)
Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang
Deep Discrete Prototype Multilabel Learning. IJCAI (2018)
Weiwei Liu, Xiao-Bo Shen, Ivor W. Tsang
Sparse Embedded k-Means Clustering. NIPS (2017)
Weiwei Liu, Ivor W. Tsang
Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions. J. Mach. Learn. Res. 18 (2017)
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 (2017)
Jing Chai, Weiwei Liu, Ivor W. Tsang, Xiao-Bo Shen
Compact Multiple-Instance Learning. CIKM (2017)
Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun
Compressed K-Means for Large-Scale Clustering. AAAI (2017)
Weiwei Liu, Ivor W. Tsang
Sparse Perceptron Decision Tree for Millions of Dimensions. AAAI (2016)
Weiwei Liu, Ivor W. Tsang
On the Optimality of Classifier Chain for Multi-label Classification. NIPS (2015)
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) (2015)
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)
Weiwei Liu, Ivor W. Tsang
Large Margin Metric Learning for Multi-Label Prediction. AAAI (2015)