Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network. - Weiwei Liu 003; Zhi-Hong Deng 001; Xiuwen Gong; Frank Jiang 001; Ivor W. Tsang (AAAI, 2015)

Large Margin Metric Learning for Multi-Label Prediction. - Weiwei Liu 003; Ivor W. Tsang (AAAI, 2015)

On the Optimality of Classifier Chain for Multi-label Classification. - Weiwei Liu 003; Ivor W. Tsang (NIPS, 2015)

Mining Top K Spread Sources for a Specific Topic and a Given Node. - Weiwei Liu 003; Zhi-Hong Deng 001; Longbing Cao; Xiaoran Xu; He Liu; Xiuwen Gong (IEEE Trans. Cybern., 2015)

Sparse Perceptron Decision Tree for Millions of Dimensions. - Weiwei Liu 003; Ivor W. Tsang (AAAI, 2016)

Compressed K-Means for Large-Scale Clustering. - Xiao-Bo Shen; Weiwei Liu 003; Ivor W. Tsang; Fumin Shen; Quan-Sen Sun (AAAI, 2017)

Compact Multiple-Instance Learning. - Jing Chai; Weiwei Liu 003; Ivor W. Tsang; Xiao-Bo Shen (CIKM, 2017)

Sparse Embedded k-Means Clustering. - Weiwei Liu 003; Xiao-Bo Shen; Ivor W. Tsang (NIPS, 2017)

Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions. - Weiwei Liu 003; Ivor W. Tsang (J. Mach. Learn. Res., 2017)

An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. - Weiwei Liu 003; Ivor W. Tsang; Klaus-Robert Müller (J. Mach. Learn. Res., 2017)

Compact Multi-Label Learning. - Xiaobo Shen 001; Weiwei Liu 003; Ivor W. Tsang; Quan-Sen Sun; Yew-Soon Ong (AAAI, 2018)

Doubly Approximate Nearest Neighbor Classification. - Weiwei Liu 003; Zhuanghua Liu; Ivor W. Tsang; Wenjie Zhang 001; Xuemin Lin 001 (AAAI, 2018)

Deep Discrete Prototype Multilabel Learning. - Xiaobo Shen 001; Weiwei Liu 003; Yong Luo 002; Yew-Soon Ong; Ivor W. Tsang (IJCAI, 2018)

Discrete Network Embedding. - Xiaobo Shen 001; Shirui Pan; Weiwei Liu 003; Yew-Soon Ong; Quan-Sen Sun (IJCAI, 2018)

Ranking Preserving Nonnegative Matrix Factorization. - Jing Wang 023; Feng Tian 006; Weiwei Liu 003; Xiao Wang 017; Wenjie Zhang 001; Kenji Yamanishi (IJCAI, 2018)

Multiview Discrete Hashing for Scalable Multimedia Search. - Xiaobo Shen 001; Fumin Shen; Li Liu 004; Yunhao Yuan 001; Weiwei Liu 003; Quan-Sen Sun (ACM Trans. Intell. Syst. Technol., 2018)

Multilabel Prediction via Cross-View Search. - Xiaobo Shen 001; Weiwei Liu 003; Ivor W. Tsang; Quan-Sen Sun; Yew-Soon Ong (IEEE Trans. Neural Networks Learn. Syst., 2018)

Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification. - Chen Chen 043; Haobo Wang 001; Weiwei Liu 003; Xingyuan Zhao; Tianlei Hu; Gang Chen 001 (AAAI, 2019)

Social Trust Network Embedding. - Pinghua Xu; Wenbin Hu 001; Jia Wu 001; Weiwei Liu 003; Bo Du 001; Jian Yang 001 (ICDM, 2019)

Sparse Extreme Multi-label Learning with Oracle Property. - Weiwei Liu 003; Xiaobo Shen 001 (ICML, 2019)

Discriminative and Correlative Partial Multi-Label Learning. - Haobo Wang 001; Weiwei Liu 003; Yang Zhao 022; Chen Zhang 020; Tianlei Hu; Gang Chen 001 (IJCAI, 2019)

Copula Multi-label Learning. - Weiwei Liu 003 (NeurIPS, 2019)

Metric Learning for Multi-Output Tasks. - Weiwei Liu 003; Donna Xu; Ivor W. Tsang; Wenjie Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Hyperspectral Imagery Classification via Stochastic HHSVMs. - Weiwei Liu 003; Xiaobo Shen 001; Bo Du 001; Ivor W. Tsang; Wenjie Zhang 001; Xuemin Lin 001 (IEEE Trans. Image Process., 2019)

Temporal Network Embedding with High-Order Nonlinear Information. - Zhenyu Qiu; Wenbin Hu 001; Jia Wu 001; Weiwei Liu 003; Bo Du 001; Xiaohua Jia (AAAI, 2020)

Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification. - Haobo Wang 001; Chen Chen 043; Weiwei Liu 003; Ke Chen 005; Tianlei Hu; Gang Chen 001 (AAAI, 2020)

Tchebycheff Procedure for Multi-task Text Classification. - Yuren Mao; Shuang Yun; Weiwei Liu 003; Bo Du 001 (ACL, 2020)

Adaptive Adversarial Multi-task Representation Learning. - Yuren Mao; Weiwei Liu 003; Xuemin Lin 001 (ICML, 2020)

Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization. - Xinjian Huang; Bo Du 001; Weiwei Liu 003 (IJCAI, 2020)

Learning From Multi-Dimensional Partial Labels. - Haobo Wang 001; Weiwei Liu 003; Yang Zhao 022; Tianlei Hu; Ke Chen 005; Gang Chen 001 (IJCAI, 2020)

Collaboration Based Multi-Label Propagation for Fraud Detection. - Haobo Wang 001; Zhao Li 007; Jiaming Huang; Pengrui Hui; Weiwei Liu 003; Tianlei Hu; Gang Chen 001 (IJCAI, 2020)

Opinion Maximization in Social Trust Networks. - Pinghua Xu; Wenbin Hu 001; Jia Wu 001; Weiwei Liu 003 (IJCAI, 2020)

Online Partial Label Learning. - Haobo Wang 001; Yuzhou Qiang; Chen Chen 043; Weiwei Liu 003; Tianlei Hu; Zhao Li 007; Gang Chen 001 (ECML/PKDD (2), 2020)

Deep Interest-Shifting Network with Meta-Embeddings for Fresh Item Recommendation. - Zhao Li 007; Haobo Wang 001; Donghui Ding; Shichang Hu; Zhen Zhang 023; Weiwei Liu 003; Jianliang Gao; Zhiqiang Zhang 010; Ji Zhang 001 (Complex., 2020)

Matrix Completion with Noise via Leveraged Sampling. - Xinjian Huang; Weiwei Liu 003; Bo Du 001 (CoRR, 2020)

Guest Editorial Special Issue on Structured Multi-Output Learning: Modeling, Algorithm, Theory, and Applications. - Weiwei Liu 003; Xiaobo Shen 001; Yew-Soon Ong; Ivor W. Tsang; Chen Gong 002; Vladimir Pavlovic 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

BanditMTL: Bandit-based Multi-task Learning for Text Classification. - Yuren Mao; Zekai Wang; Weiwei Liu 003; Xuemin Lin 001; Wenbin Hu 001 (ACL/IJCNLP (1), 2021)

Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information. - Chuang Liu 008; Jia Wu 001; Weiwei Liu 003; Wenbin Hu 001 (Neural Networks, 2021)

MetaWeighting: Learning to Weight Tasks in Multi-Task Learning. - Yuren Mao; Zekai Wang; Weiwei Liu 003; Xuemin Lin 001; Pengtao Xie (ACL (Findings), 2022)

Robustness Verification for Contrastive Learning. - Zekai Wang; Weiwei Liu 003 (ICML, 2022)

Defending Against Adversarial Attacks via Neural Dynamic System. - Xiyuan Li; Xin Zou 002; Weiwei Liu 003 (NeurIPS, 2022)

On the Tradeoff Between Robustness and Fairness. - Xinsong Ma; Zekai Wang; Weiwei Liu 003 (NeurIPS, 2022)

CLNode: Curriculum Learning for Node Classification. - Xiaowen Wei; Weiwei Liu 003; Yibing Zhan; Bo Du 001; Wenbin Hu 001 (CoRR, 2022)

Signed network representation with novel node proximity evaluation. - Pinghua Xu; Wenbin Hu 001; Jia Wu 001; Weiwei Liu 003 (Neural Networks, 2022)

The Emerging Trends of Multi-Label Learning. - Weiwei Liu 003; Haobo Wang 001; Xiaobo Shen 001; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Better Diffusion Models Further Improve Adversarial Training. - Zekai Wang; Tianyu Pang; Chao Du; Min Lin; Weiwei Liu 003; Shuicheng Yan (ICML, 2023)

Delving into Noisy Label Detection with Clean Data. - Chenglin Yu; Xinsong Ma; Weiwei Liu 003 (ICML, 2023)

Deep Partial Multi-Label Learning with Graph Disambiguation. - Haobo Wang 001; Shisong Yang; Gengyu Lyu; Weiwei Liu 003; Tianlei Hu; Ke Chen 005; Songhe Feng; Gang Chen 001 (IJCAI, 2023)

Graph Convolutional Incomplete Multi-modal Hashing. - Xiaobo Shen 001; Yinfan Chen; Shirui Pan; Weiwei Liu 003; Yuhui Zheng (ACM Multimedia, 2023)

On the Adversarial Robustness of Out-of-distribution Generalization Models. - Xin Zou 002; Weiwei Liu 003 (NeurIPS, 2023)

RVCL: Evaluating the Robustness of Contrastive Learning via Verification. - Zekai Wang; Weiwei Liu 003 (J. Mach. Learn. Res., 2023)

Generalization Bounds for Adversarial Contrastive Learning. - Xin Zou 002; Weiwei Liu 003 (J. Mach. Learn. Res., 2023)

Signed Network Representation by Preserving Multi-Order Signed Proximity. - Pinghua Xu; Wenbin Hu 001; Jia Wu 001; Weiwei Liu 003; Yang Yang; Philip S. Yu (IEEE Trans. Knowl. Data Eng., 2023)

Compact network embedding for fast node classification. - Xiaobo Shen 001; Yew-Soon Ong; Zheng Mao; Shirui Pan; Weiwei Liu 003; Yuhui Zheng (Pattern Recognit., 2023)

Task Variance Regularized Multi-Task Learning. - Yuren Mao; Zekai Wang; Weiwei Liu 003; Xuemin Lin 001; Wenbin Hu 001 (IEEE Trans. Knowl. Data Eng., 2023)

DRF: Improving Certified Robustness via Distributional Robustness Framework. - Zekai Wang; Zhengyu Zhou; Weiwei Liu 003 (AAAI, 2024)

Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data. - Xin Zou 002; Weiwei Liu 003 (AAAI, 2024)

A Provable Decision Rule for Out-of-Distribution Detection. - Xinsong Ma; Xin Zou 002; Weiwei Liu 003 (ICML, 2024)

Sequential Kernel Goodness-of-fit Testing. - Zhengyu Zhou; Weiwei Liu 003 (ICML, 2024)

Zero-shot Learning for Preclinical Drug Screening. - Kun Li 009; Weiwei Liu 003; Yong Luo 002; Xiantao Cai; Jia Wu 001; Wenbin Hu 001 (IJCAI, 2024)

A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers. - Xin Zou 002; Zhengyu Zhou; Jingyuan Xu; Weiwei Liu 003 (NeurIPS, 2024)

Text-Guided Multi-Property Molecular Optimization with a Diffusion Language Model. - Yida Xiong; Kun Li 009; Weiwei Liu 003; Jia Wu 001; Bo Du 001; Shirui Pan; Wenbin Hu 001 (CoRR, 2024)

On the Value of Head Labels in Multi-Label Text Classification. - Haobo Wang 001; Cheng Peng 011; Hede Dong; Lei Feng 006; Weiwei Liu 003; Tianlei Hu; Ke Chen 005; Gang Chen 001 (ACM Trans. Knowl. Discov. Data, 2024)

Leveraged Matrix Completion With Noise. - Xinjian Huang; Weiwei Liu 003; Bo Du 001; Dacheng Tao (IEEE Trans. Cybern., 2024)

Class-Imbalanced-Aware Distantly Supervised Named Entity Recognition. - Yuren Mao; Yu Hao 003; Weiwei Liu 003; Xuemin Lin 001; Xin Cao 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

SAC-BL: A hypothesis testing framework for unsupervised visual anomaly detection and location. - Xinsong Ma; Jie Wu; Weiwei Liu 003 (Neural Networks, 2025)

Residual network with self-adaptive time step size. - Xiyuan Li; Xin Zou 002; Weiwei Liu 003 (Pattern Recognit., 2025)

Graph Convolutional Multi-Label Hashing for Cross-Modal Retrieval. - Xiaobo Shen 001; Yinfan Chen; Weiwei Liu 003; Yuhui Zheng; Quan-Sen Sun; Shirui Pan (IEEE Trans. Neural Networks Learn. Syst., 2025)