Weiwei Liu

According to our database, Weiwei Liu authored at least 51 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

DRF: Improving Certified Robustness via Distributional Robustness Framework.

Zekai Wang, Zhengyu Zhou, Weiwei Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Task Variance Regularized Multi-Task Learning.

Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu

IEEE Trans. Knowl. Data Eng., August, 2023

Compact network embedding for fast node classification.

Xiaobo Shen, Yew-Soon Ong, Zheng Mao, Shirui Pan, Weiwei Liu, Yuhui Zheng

Pattern Recognit., April, 2023

Signed Network Representation by Preserving Multi-Order Signed Proximity.

Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Yang Yang, Philip S. Yu

IEEE Trans. Knowl. Data Eng., March, 2023

Deep Partial Multi-Label Learning with Graph Disambiguation.

Haobo Wang, Shisong Yang, Gengyu Lyu, Weiwei Liu, Tianlei Hu, Ke Chen, Songhe Feng, Gang Chen

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Delving into Noisy Label Detection with Clean Data.

Chenglin Yu, Xinsong Ma, Weiwei Liu

Proceedings of the International Conference on Machine Learning, 2023

Better Diffusion Models Further Improve Adversarial Training.

Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan

Proceedings of the International Conference on Machine Learning, 2023

2022

The Emerging Trends of Multi-Label Learning.

Weiwei Liu, Haobo Wang, Xiaobo Shen, Ivor W. Tsang

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Signed network representation with novel node proximity evaluation.

Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu

Neural Networks, 2022

CLNode: Curriculum Learning for Node Classification.

Xiaowen Wei, Weiwei Liu, Yibing Zhan, Bo Du, Wenbin Hu

CoRR, 2022

On the Tradeoff Between Robustness and Fairness.

Xinsong Ma, Zekai Wang, Weiwei Liu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Robustness Verification for Contrastive Learning.

Zekai Wang, Weiwei Liu

Proceedings of the International Conference on Machine Learning, 2022

MetaWeighting: Learning to Weight Tasks in Multi-Task Learning.

Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Pengtao Xie

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information.

Chuang Liu, Jia Wu, Weiwei Liu, Wenbin Hu

Neural Networks, 2021

BanditMTL: Bandit-based Multi-task Learning for Text Classification.

Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Guest Editorial Special Issue on Structured Multi-Output Learning: Modeling, Algorithm, Theory, and Applications.

Weiwei Liu, Xiaobo Shen, Yew-Soon Ong, Ivor W. Tsang, Chen Gong, Vladimir Pavlovic

IEEE Trans. Neural Networks Learn. Syst., 2020

Matrix Completion with Noise via Leveraged Sampling.

Xinjian Huang, Weiwei Liu, Bo Du

CoRR, 2020

Deep Interest-Shifting Network with Meta-Embeddings for Fresh Item Recommendation.

Zhao Li, Haobo Wang, Donghui Ding, Shichang Hu, Zhen Zhang, Weiwei Liu, Jianliang Gao, Zhiqiang Zhang, Ji Zhang

Complex., 2020

Online Partial Label Learning.

Haobo Wang, Yuzhou Qiang, Chen Chen, Weiwei Liu, Tianlei Hu, Zhao Li, Gang Chen

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Opinion Maximization in Social Trust Networks.

Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Collaboration Based Multi-Label Propagation for Fraud Detection.

Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Learning From Multi-Dimensional Partial Labels.

Haobo Wang, Weiwei Liu, Yang Zhao, Tianlei Hu, Ke Chen, Gang Chen

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization.

Xinjian Huang, Bo Du, Weiwei Liu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Adaptive Adversarial Multi-task Representation Learning.

Yuren Mao, Weiwei Liu, Xuemin Lin

Proceedings of the 37th International Conference on Machine Learning, 2020

Tchebycheff Procedure for Multi-task Text Classification.

Yuren Mao, Shuang Yun, Weiwei Liu, Bo Du

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification.

Haobo Wang, Chen Chen, Weiwei Liu, Ke Chen, Tianlei Hu, Gang Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Temporal Network Embedding with High-Order Nonlinear Information.

Zhenyu Qiu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Xiaohua Jia

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Hyperspectral Imagery Classification via Stochastic HHSVMs.

Weiwei Liu, Xiaobo Shen, Bo Du, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin

IEEE Trans. Image Process., 2019

Metric Learning for Multi-Output Tasks.

Weiwei Liu, Donna Xu, Ivor W. Tsang, Wenjie Zhang

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Copula Multi-label Learning.

Weiwei Liu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Discriminative and Correlative Partial Multi-Label Learning.

Haobo Wang, Weiwei Liu, Yang Zhao, Chen Zhang, Tianlei Hu, Gang Chen

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Sparse Extreme Multi-label Learning with Oracle Property.

Weiwei Liu, Xiaobo Shen

Proceedings of the 36th International Conference on Machine Learning, 2019

Social Trust Network Embedding.

Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Jian Yang

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification.

Chen Chen, Haobo Wang, Weiwei Liu, Xingyuan Zhao, Tianlei Hu, Gang Chen

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Multilabel Prediction via Cross-View Search.

Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong

IEEE Trans. Neural Networks Learn. Syst., 2018

Multiview Discrete Hashing for Scalable Multimedia Search.

Xiaobo Shen, Fumin Shen, Li Liu, Yunhao Yuan, Weiwei Liu, Quan-Sen Sun

ACM Trans. Intell. Syst. Technol., 2018

Ranking Preserving Nonnegative Matrix Factorization.

Jing Wang, Feng Tian, Weiwei Liu, Xiao Wang, Wenjie Zhang, Kenji Yamanishi

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Discrete Network Embedding.

Xiaobo Shen, Shirui Pan, Weiwei Liu, Yew-Soon Ong, Quan-Sen Sun

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Deep Discrete Prototype Multilabel Learning.

Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Doubly Approximate Nearest Neighbor Classification.

Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Compact Multi-Label Learning.

Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels.

Weiwei Liu, Ivor W. Tsang, Klaus-Robert Müller

J. Mach. Learn. Res., 2017

Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions.

Weiwei Liu, Ivor W. Tsang

J. Mach. Learn. Res., 2017

Sparse Embedded k-Means Clustering.

Weiwei Liu, Xiao-Bo Shen, Ivor W. Tsang

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Compact Multiple-Instance Learning.

Jing Chai, Weiwei Liu, Ivor W. Tsang, Xiao-Bo Shen

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Compressed K-Means for Large-Scale Clustering.

Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Sparse Perceptron Decision Tree for Millions of Dimensions.

Weiwei Liu, Ivor W. Tsang

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Mining Top K Spread Sources for a Specific Topic and a Given Node.

Weiwei Liu, Zhi-Hong Deng, Longbing Cao, Xiaoran Xu, He Liu, Xiuwen Gong

IEEE Trans. Cybern., 2015

On the Optimality of Classifier Chain for Multi-label Classification.

Weiwei Liu, Ivor W. Tsang

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Large Margin Metric Learning for Multi-Label Prediction.

Weiwei Liu, Ivor W. Tsang

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network.

Weiwei Liu, Zhi-Hong Deng, Xiuwen Gong, Frank Jiang, Ivor W. Tsang

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015