Weiwei Liu - RankMe

85 papers A* 45A 1Journal 34Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Unified Decision Rule for Generalized Out-of-Distribution Detection. IEEE Trans. Pattern Anal. Mach. Intell. Xinsong Ma, Jie Wu, Xin Zou, Weiwei Liu
2026	A*	`conf`	On the Robustness of Bandit Multiple Testing. AAAI Zhengyu Zhou, Weiwei Liu
2026	A*	`conf`	Rademacher Complexity for Distributionally Robust Learning. AAAI Zhengyu Zhou, Weiwei Liu
2025	A*	`conf`	A Closer Look at Generalized BH Algorithm for Out-of-Distribution Detection. ICML Xinsong Ma, Jie Wu, Weiwei Liu
2025	A*	`conf`	An Error Analysis of Flow Matching for Deep Generative Modeling. ICML Zhengyu Zhou, Weiwei Liu
2025	A*	`conf`	An Online Statistical Framework for Out-of-Distribution Detection. ICML Xinsong Ma, Xin Zou, Weiwei Liu
2025	J	`jnl`	Graph Convolutional Multi-Label Hashing for Cross-Modal Retrieval. IEEE Trans. Neural Networks Learn. Syst. Xiaobo Shen, Yinfan Chen, Weiwei Liu, Yuhui Zheng, Quan-Sen Sun, Shirui Pan
2025	A*	`conf`	Nonconvex Theory of M-estimators with Decomposable Regularizers. ICML Weiwei Liu
2025	J	`jnl`	Residual network with self-adaptive time step size. Pattern Recognit. Xiyuan Li, Xin Zou, Weiwei Liu
2025	J	`jnl`	SAC-BL: A hypothesis testing framework for unsupervised visual anomaly detection and location. Neural Networks Xinsong Ma, Jie Wu, Weiwei Liu
2025	A*	`conf`	Towards Understanding Catastrophic Forgetting in Two-layer Convolutional Neural Networks. ICML Boqi Li, Youjun Wang, Weiwei Liu
2024	A*	`conf`	A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers. NeurIPS Xin Zou, Zhengyu Zhou, Jingyuan Xu, Weiwei Liu
2024	A*	`conf`	A Provable Decision Rule for Out-of-Distribution Detection. ICML Xinsong Ma, Xin Zou, Weiwei Liu
2024	A*	`conf`	A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks. ICML Boqi Li, Weiwei Liu
2024	J	`jnl`	Class-Imbalanced-Aware Distantly Supervised Named Entity Recognition. IEEE Trans. Neural Networks Learn. Syst. Yuren Mao, Yu Hao, Weiwei Liu, Xuemin Lin, Xin Cao
2024	A*	`conf`	Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data. AAAI Xin Zou, Weiwei Liu
2024	J	`jnl`	Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data. CoRR Xin Zou, Weiwei Liu
2024	A*	`conf`	DRF: Improving Certified Robustness via Distributional Robustness Framework. AAAI Zekai Wang, Zhengyu Zhou, Weiwei Liu
2024	J	`jnl`	Leveraged Matrix Completion With Noise. IEEE Trans. Cybern. Xinjian Huang, Weiwei Liu, Bo Du, Dacheng Tao
2024	J	`jnl`	On the Value of Head Labels in Multi-Label Text Classification. ACM Trans. Knowl. Discov. Data Haobo Wang, Cheng Peng, Hede Dong, Lei Feng, Weiwei Liu, Tianlei Hu, Ke Chen, Gang Chen
2024	A*	`conf`	Sequential Kernel Goodness-of-fit Testing. ICML Zhengyu Zhou, Weiwei Liu
2024	J	`jnl`	Text-Guided Multi-Property Molecular Optimization with a Diffusion Language Model. CoRR Yida Xiong, Kun Li, Weiwei Liu, Jia Wu, Bo Du, Shirui Pan, Wenbin Hu
2024	A*	`conf`	Zero-shot Learning for Preclinical Drug Screening. IJCAI Kun Li, Weiwei Liu, Yong Luo, Xiantao Cai, Jia Wu, Wenbin Hu
2023	A*	`conf`	Better Diffusion Models Further Improve Adversarial Training. ICML Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan
2023	J	`jnl`	Better Diffusion Models Further Improve Adversarial Training. CoRR Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, Shuicheng Yan
2023	J	`jnl`	Compact network embedding for fast node classification. Pattern Recognit. Xiaobo Shen, Yew-Soon Ong, Zheng Mao, Shirui Pan, Weiwei Liu, Yuhui Zheng
2023	A*	`conf`	Deep Partial Multi-Label Learning with Graph Disambiguation. IJCAI Haobo Wang, Shisong Yang, Gengyu Lyu, Weiwei Liu, Tianlei Hu, Ke Chen, Songhe Feng, Gang Chen
2023	J	`jnl`	Deep Partial Multi-Label Learning with Graph Disambiguation. CoRR Haobo Wang, Shisong Yang, Gengyu Lyu, Weiwei Liu, Tianlei Hu, Ke Chen, Songhe Feng, Gang Chen
2023	A*	`conf`	Delving into Noisy Label Detection with Clean Data. ICML Chenglin Yu, Xinsong Ma, Weiwei Liu
2023	J	`jnl`	Generalization Bounds for Adversarial Contrastive Learning. CoRR Xin Zou, Weiwei Liu
2023	J	`jnl`	Generalization Bounds for Adversarial Contrastive Learning. J. Mach. Learn. Res. Xin Zou, Weiwei Liu
2023	A*	`conf`	Graph Convolutional Incomplete Multi-modal Hashing. ACM Multimedia Xiaobo Shen, Yinfan Chen, Shirui Pan, Weiwei Liu, Yuhui Zheng
2023	A*	`conf`	On the Adversarial Robustness of Out-of-distribution Generalization Models. NeurIPS Xin Zou, Weiwei Liu
2023	J	`jnl`	RVCL: Evaluating the Robustness of Contrastive Learning via Verification. J. Mach. Learn. Res. Zekai Wang, Weiwei Liu
2023	J	`jnl`	Signed Network Representation by Preserving Multi-Order Signed Proximity. IEEE Trans. Knowl. Data Eng. Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Yang Yang, Philip S. Yu
2023	J	`jnl`	Task Variance Regularized Multi-Task Learning. IEEE Trans. Knowl. Data Eng. Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu
2023	A*	`conf`	WAT: Improve the Worst-Class Robustness in Adversarial Training. AAAI Boqi Li, Weiwei Liu
2023	J	`jnl`	WAT: Improve the Worst-class Robustness in Adversarial Training. CoRR Boqi Li, Weiwei Liu
2022	J	`jnl`	CLNode: Curriculum Learning for Node Classification. CoRR Xiaowen Wei, Weiwei Liu, Yibing Zhan, Bo Du, Wenbin Hu
2022	A*	`conf`	Defending Against Adversarial Attacks via Neural Dynamic System. NeurIPS Xiyuan Li, Xin Zou, Weiwei Liu
2022	—	`conf`	MetaWeighting: Learning to Weight Tasks in Multi-Task Learning. ACL (Findings) Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Pengtao Xie
2022	A*	`conf`	On the Tradeoff Between Robustness and Fairness. NeurIPS Xinsong Ma, Zekai Wang, Weiwei Liu
2022	A*	`conf`	Robustness Verification for Contrastive Learning. ICML Zekai Wang, Weiwei Liu
2022	J	`jnl`	Signed network representation with novel node proximity evaluation. Neural Networks Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu
2022	J	`jnl`	The Emerging Trends of Multi-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. Weiwei Liu, Haobo Wang, Xiaobo Shen, Ivor W. Tsang
2021	—	`conf`	BanditMTL: Bandit-based Multi-task Learning for Text Classification. ACL/IJCNLP (1) Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Wenbin Hu
2021	J	`jnl`	Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information. Neural Networks Chuang Liu, Jia Wu, Weiwei Liu, Wenbin Hu
2020	A*	`conf`	Adaptive Adversarial Multi-task Representation Learning. ICML Yuren Mao, Weiwei Liu, Xuemin Lin
2020	A*	`conf`	Collaboration Based Multi-Label Propagation for Fraud Detection. IJCAI Haobo Wang, Zhao Li, Jiaming Huang, Pengrui Hui, Weiwei Liu, Tianlei Hu, Gang Chen
2020	J	`jnl`	Deep Interest-Shifting Network with Meta-Embeddings for Fresh Item Recommendation. Complex. Zhao Li, Haobo Wang, Donghui Ding, Shichang Hu, Zhen Zhang, Weiwei Liu, Jianliang Gao, Zhiqiang Zhang, Ji Zhang
2020	J	`jnl`	Guest Editorial Special Issue on Structured Multi-Output Learning: Modeling, Algorithm, Theory, and Applications. IEEE Trans. Neural Networks Learn. Syst. Weiwei Liu, Xiaobo Shen, Yew-Soon Ong, Ivor W. Tsang, Chen Gong, Vladimir Pavlovic
2020	A*	`conf`	Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification. AAAI Haobo Wang, Chen Chen, Weiwei Liu, Ke Chen, Tianlei Hu, Gang Chen
2020	A*	`conf`	Learning From Multi-Dimensional Partial Labels. IJCAI Haobo Wang, Weiwei Liu, Yang Zhao, Tianlei Hu, Ke Chen, Gang Chen
2020	J	`jnl`	Matrix Completion with Noise via Leveraged Sampling. CoRR Xinjian Huang, Weiwei Liu, Bo Du
2020	A*	`conf`	Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization. IJCAI Xinjian Huang, Bo Du, Weiwei Liu
2020	—	`conf`	Online Partial Label Learning. ECML/PKDD (2) Haobo Wang, Yuzhou Qiang, Chen Chen, Weiwei Liu, Tianlei Hu, Zhao Li, Gang Chen
2020	A*	`conf`	Opinion Maximization in Social Trust Networks. IJCAI Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu
2020	J	`jnl`	Opinion Maximization in Social Trust Networks. CoRR Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu
2020	A*	`conf`	Tchebycheff Procedure for Multi-task Text Classification. ACL Yuren Mao, Shuang Yun, Weiwei Liu, Bo Du
2020	A*	`conf`	Temporal Network Embedding with High-Order Nonlinear Information. AAAI Zhenyu Qiu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Xiaohua Jia
2020	J	`jnl`	The Emerging Trends of Multi-Label Learning. CoRR Weiwei Liu, Xiaobo Shen, Haobo Wang, Ivor W. Tsang
2019	A*	`conf`	Copula Multi-label Learning. NeurIPS Weiwei Liu
2019	A*	`conf`	Discriminative and Correlative Partial Multi-Label Learning. IJCAI Haobo Wang, Weiwei Liu, Yang Zhao, Chen Zhang, Tianlei Hu, Gang Chen
2019	J	`jnl`	Hyperspectral Imagery Classification via Stochastic HHSVMs. IEEE Trans. Image Process. Weiwei Liu, Xiaobo Shen, Bo Du, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin
2019	J	`jnl`	Metric Learning for Multi-Output Tasks. IEEE Trans. Pattern Anal. Mach. Intell. Weiwei Liu, Donna Xu, Ivor W. Tsang, Wenjie Zhang
2019	A*	`conf`	Social Trust Network Embedding. ICDM Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du, Jian Yang
2019	A*	`conf`	Sparse Extreme Multi-label Learning with Oracle Property. ICML Weiwei Liu, Xiaobo Shen
2019	A*	`conf`	Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification. AAAI Chen Chen, Haobo Wang, Weiwei Liu, Xingyuan Zhao, Tianlei Hu, Gang Chen
2018	A*	`conf`	Compact Multi-Label Learning. AAAI Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong
2018	A*	`conf`	Deep Discrete Prototype Multilabel Learning. IJCAI Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang
2018	A*	`conf`	Discrete Network Embedding. IJCAI Xiaobo Shen, Shirui Pan, Weiwei Liu, Yew-Soon Ong, Quan-Sen Sun
2018	A*	`conf`	Doubly Approximate Nearest Neighbor Classification. AAAI Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin
2018	J	`jnl`	Multilabel Prediction via Cross-View Search. IEEE Trans. Neural Networks Learn. Syst. Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong
2018	J	`jnl`	Multiview Discrete Hashing for Scalable Multimedia Search. ACM Trans. Intell. Syst. Technol. Xiaobo Shen, Fumin Shen, Li Liu, Yunhao Yuan, Weiwei Liu, Quan-Sen Sun
2018	A*	`conf`	Ranking Preserving Nonnegative Matrix Factorization. IJCAI Jing Wang, Feng Tian, Weiwei Liu, Xiao Wang, Wenjie Zhang, Kenji Yamanishi
2017	J	`jnl`	An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. J. Mach. Learn. Res. Weiwei Liu, Ivor W. Tsang, Klaus-Robert Müller
2017	A	`conf`	Compact Multiple-Instance Learning. CIKM Jing Chai, Weiwei Liu, Ivor W. Tsang, Xiao-Bo Shen
2017	A*	`conf`	Compressed K-Means for Large-Scale Clustering. AAAI Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun
2017	J	`jnl`	Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions. J. Mach. Learn. Res. Weiwei Liu, Ivor W. Tsang
2017	—	`conf`	Sparse Embedded k-Means Clustering. NIPS Weiwei Liu, Xiao-Bo Shen, Ivor W. Tsang
2016	A*	`conf`	Sparse Perceptron Decision Tree for Millions of Dimensions. AAAI Weiwei Liu, Ivor W. Tsang
2015	A*	`conf`	Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network. AAAI Weiwei Liu, Zhi-Hong Deng, Xiuwen Gong, Frank Jiang, Ivor W. Tsang
2015	A*	`conf`	Large Margin Metric Learning for Multi-Label Prediction. AAAI Weiwei Liu, Ivor W. Tsang
2015	J	`jnl`	Mining Top K Spread Sources for a Specific Topic and a Given Node. IEEE Trans. Cybern. Weiwei Liu, Zhi-Hong Deng, Longbing Cao, Xiaoran Xu, He Liu, Xiuwen Gong
2015	—	`conf`	On the Optimality of Classifier Chain for Multi-label Classification. NIPS Weiwei Liu, Ivor W. Tsang