Qimai Li

According to our database, Qimai Li authored at least 23 papers between 2018 and 2023.

Collaborative distances:

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

2023

Adaptive Graph Convolution Methods for Attributed Graph Clustering.

Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu, Xianchao Zhang

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

Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model.

Kai Yang, Jian Tao, Jiafei Lyu, Chunjiang Ge, Jiaxin Chen, Qimai Li, Weihan Shen, Xiaolong Zhu, Xiu Li

CoRR, 2023

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning.

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

CoRR, 2023

Simple yet Effective Gradient-Free Graph Convolutional Networks.

Yulin Zhu, Xing Ai, Qimai Li, Xiao-Ming Wu, Kai Zhou

CoRR, 2023

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors.

Han Liu, Xingshuo Huang, Xiaotong Zhang, Qimai Li, Fenglong Ma, Wei Wang, Hongyang Chen, Hong Yu, Xianchao Zhang

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

Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning.

Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks.

Quanyu Dai, Xiao-Ming Wu, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Dan Wang, Guli Lin, Keping Yang

Pattern Recognit., 2022

Multi-Agent Path Finding via Tree LSTM.

Yuhao Jiang, Kunjie Zhang, Qimai Li, Jiaxin Chen, Xiaolong Zhu

CoRR, 2022

Modeling User Behavior with Graph Convolution for Personalized Product Search.

Fan Lu, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang

CoRR, 2022

Modeling User Behavior with Graph Convolution for Personalized Product Search.

Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

2021

RPC: Representative possible world based consistent clustering algorithm for uncertain data.

Han Liu, Xiaotong Zhang, Xianchao Zhang, Qimai Li, Xiao-Ming Wu

Comput. Commun., 2021

Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs.

Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

A Closer Look at the Training Strategy for Modern Meta-Learning.

Jiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification.

Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam

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

2019

Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning.

Han Liu, Xianchao Zhang, Xiaotong Zhang, Qimai Li, Xiao-Ming Wu

CoRR, 2019

Attributed Graph Learning with 2-D Graph Convolution.

Qimai Li, Xiaotong Zhang, Han Liu, Xiao-Ming Wu

CoRR, 2019

Generalized Label Propagation Methods for Semi-Supervised Learning.

Qimai Li, Xiao-Ming Wu, Zhichao Guan

CoRR, 2019

Attributed Graph Clustering via Adaptive Graph Convolution.

Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu

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

Reconstructing Capsule Networks for Zero-shot Intent Classification.

Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu, Albert Y. S. Lam

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Label Efficient Semi-Supervised Learning via Graph Filtering.

Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Large Margin Few-Shot Learning.

Yong Wang, Xiao-Ming Wu, Qimai Li, Jiatao Gu, Wangmeng Xiang, Lei Zhang, Victor O. K. Li

CoRR, 2018

Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning.

Qimai Li, Zhichao Han, Xiao-Ming Wu

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