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2020 – today
- 2023
[j3]Xiaotong Zhang
, Han Liu, Qimai Li, Xiao-Ming Wu, Xianchao Zhang:
Adaptive Graph Convolution Methods for Attributed Graph Clustering. IEEE Trans. Knowl. Data Eng. 35(12): 12384-12399 (2023)- [c11]Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu:
Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning. ICLR 2023 - [c10]Han Liu, Xingshuo Huang, Xiaotong Zhang, Qimai Li, Fenglong Ma, Wei Wang, Hongyang Chen, Hong Yu, Xianchao Zhang:
Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors. IJCAI 2023: 1195-1203 - [c9]Joseph Suarez, David Bloomin, Kyoung Whan Choe, Hao Xiang Li, Ryan Sullivan, Nishaanth Kanna, Daniel Scott, Rose S. Shuman, Herbie Bradley, Louis Castricato, Phillip Isola, Chenghui Yu, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu:
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. NeurIPS 2023 - [i13]Yulin Zhu, Xing Ai, Qimai Li, Xiao-Ming Wu, Kai Zhou:
Simple yet Effective Gradient-Free Graph Convolutional Networks. CoRR abs/2302.00371 (2023) - [i12]Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu:
Recon: Reducing Conflicting Gradients from the Root for Multi-Task Learning. CoRR abs/2302.11289 (2023) - [i11]Han Liu, Xingshuo Huang, Xiaotong Zhang, Qimai Li, Fenglong Ma, Wei Wang, Hongyang Chen, Hong Yu, Xianchao Zhang:
Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors. CoRR abs/2310.19038 (2023) - [i10]Joseph Suárez, Phillip Isola, Kyoung Whan Choe, David Bloomin, Hao Xiang Li, Nikhil Pinnaparaju, Nishaanth Kanna, Daniel Scott, Ryan Sullivan, Rose S. Shuman, Lucas de Alcântara, Herbie Bradley, Louis Castricato, Kirsty You, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu:
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. CoRR abs/2311.03736 (2023) - [i9]Kai Yang, Jian Tao, Jiafei Lyu, Chunjiang Ge, Jiaxin Chen, Qimai Li, Weihan Shen, Xiaolong Zhu, Xiu Li:
Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model. CoRR abs/2311.13231 (2023) - 2022
- [j2]Quanyu Dai, Xiao-Ming Wu, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Dan Wang, Guli Lin, Keping Yang:
Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks. Pattern Recognit. 128: 108628 (2022) - [c8]Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang:
Modeling User Behavior with Graph Convolution for Personalized Product Search. WWW 2022: 203-212 - [i8]Fan Lu, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang:
Modeling User Behavior with Graph Convolution for Personalized Product Search. CoRR abs/2202.06081 (2022) - [i7]Yuhao Jiang, Kunjie Zhang, Qimai Li, Jiaxin Chen, Xiaolong Zhu:
Multi-Agent Path Finding via Tree LSTM. CoRR abs/2210.12933 (2022) - 2021
- [j1]Han Liu, Xiaotong Zhang, Xianchao Zhang, Qimai Li, Xiao-Ming Wu:
RPC: Representative possible world based consistent clustering algorithm for uncertain data. Comput. Commun. 176: 128-137 (2021) - [c7]Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu:
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs. KDD 2021: 953-963 - 2020
- [c6]Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam:
Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification. ACL 2020: 1050-1060 - [c5]Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung:
A Closer Look at the Training Strategy for Modern Meta-Learning. NeurIPS 2020
2010 – 2019
- 2019
- [c4]Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan:
Label Efficient Semi-Supervised Learning via Graph Filtering. CVPR 2019: 9582-9591 - [c3]Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu, Albert Y. S. Lam:
Reconstructing Capsule Networks for Zero-shot Intent Classification. EMNLP/IJCNLP (1) 2019: 4798-4808 - [c2]Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu:
Attributed Graph Clustering via Adaptive Graph Convolution. IJCAI 2019: 4327-4333 - [i6]Qimai Li, Xiao-Ming Wu, Zhichao Guan:
Generalized Label Propagation Methods for Semi-Supervised Learning. CoRR abs/1901.09993 (2019) - [i5]Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu:
Attributed Graph Clustering via Adaptive Graph Convolution. CoRR abs/1906.01210 (2019) - [i4]Qimai Li, Xiaotong Zhang, Han Liu, Xiao-Ming Wu:
Attributed Graph Learning with 2-D Graph Convolution. CoRR abs/1909.12038 (2019) - [i3]Han Liu, Xianchao Zhang, Xiaotong Zhang, Qimai Li, Xiao-Ming Wu:
Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning. CoRR abs/1909.12514 (2019) - 2018
- [c1]Qimai Li, Zhichao Han, Xiao-Ming Wu:
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning. AAAI 2018: 3538-3545 - [i2]Qimai Li, Zhichao Han, Xiao-Ming Wu:
Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning. CoRR abs/1801.07606 (2018) - [i1]Yong Wang, Xiao-Ming Wu, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang, Victor O. K. Li:
Large Margin Few-Shot Learning. CoRR abs/1807.02872 (2018)
Coauthor Index
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