Lanqing Li

According to our database, Lanqing Li authored at least 30 papers between 2020 and 2024.

Collaborative distances:

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

2024

Solving the non-submodular network collapse problems via Decision Transformer.

Kaili Ma, Han Yang, Shanchao Yang, Kangfei Zhao, Lanqing Li, Yongqiang Chen, Junzhou Huang, James Cheng, Yu Rong

Neural Networks, 2024

Scrutinize What We Ignore: Reining Task Representation Shift In Context-Based Offline Meta Reinforcement Learning.

Hai Zhang, Boyuan Zheng, Anqi Guo, Tianying Ji, Pheng-Ann Heng, Junqiao Zhao, Lanqing Li

CoRR, 2024

An Autonomous Large Language Model Agent for Chemical Literature Data Mining.

Kexin Chen, Hanqun Cao, Junyou Li, Yuyang Du, Menghao Guo, Xin Zeng, Lanqing Li, Jiezhong Qiu, Pheng-Ann Heng, Guangyong Chen

CoRR, 2024

Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning.

Lanqing Li, Hai Zhang, Xinyu Zhang, Shatong Zhu, Junqiao Zhao, Pheng-Ann Heng

CoRR, 2024

2023

Dynamics Adapted Imitation Learning.

Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao

Trans. Mach. Learn. Res., 2023

Towards an Automatic AI Agent for Reaction Condition Recommendation in Chemical Synthesis.

Kexin Chen, Junyou Li, Kunyi Wang, Yuyang Du, Jiahui Yu, Jiamin Lu, Lanqing Li, Jiezhong Qiu, Qun Fang, Pheng-Ann Heng, Guangyong Chen

CoRR, 2023

MolKD: Distilling Cross-Modal Knowledge in Chemical Reactions for Molecular Property Prediction.

Liang Zeng, Lanqing Li, Jian Li

CoRR, 2023

Reweighted Mixup for Subpopulation Shift.

Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao

CoRR, 2023

Deploying Offline Reinforcement Learning with Human Feedback.

Ziniu Li, Ke Xu, Liu Liu, Lanqing Li, Deheng Ye, Peilin Zhao

CoRR, 2023

Energy Saving Evaluation Method for Energy Storage Technologies Based on the Intimate Data Method of Machine Learning.

Yulin Zhao, Chong Sun, Lanqing Li, Yifeng Li, Hang Zhou

Proceedings of the 2023 International Conference on Power, 2023

Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition.

Zhipeng Zhou, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Wei Gong

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

On the Pitfall of Mixup for Uncertainty Calibration.

Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations.

Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Handling Missing Data via Max-Entropy Regularized Graph Autoencoder.

Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification.

Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery.

Lanqing Li, Liang Zeng, Ziqi Gao, Shen Yuan, Yatao Bian, Bingzhe Wu, Hengtong Zhang, Chan Lu, Yang Yu, Wei Liu, Hongteng Xu, Jia Li, Peilin Zhao, Pheng-Ann Heng

CoRR, 2022

Robust Imitation Learning from Corrupted Demonstrations.

Liu Liu, Ziyang Tang, Lanqing Li, Dijun Luo

CoRR, 2022

DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations.

Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Long-Kai Huang, Tingyang Xu, Yu Rong, Lanqing Li, Jie Ren, Ding Xue, Houtim Lai, Shaoyong Xu, Jing Feng, Wei Liu, Ping Luo, Shuigeng Zhou, Junzhou Huang, Peilin Zhao, Yatao Bian

CoRR, 2022

Value Penalized Q-Learning for Recommender Systems.

Chengqian Gao, Ke Xu, Kuangqi Zhou, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup.

Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao

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

Local Augmentation for Graph Neural Networks.

Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

Proceedings of the International Conference on Machine Learning, 2022

iGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control.

Xiaoyan Cao, Yao Yao, Lanqing Li, Wanpeng Zhang, Zhicheng An, Zhong Zhang, Li Xiao, Shihui Guo, Xiaoyu Cao, Meihong Wu, Dijun Luo

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Local Augmentation for Graph Neural Networks.

Songtao Liu, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

CoRR, 2021

IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control.

Xiaoyan Cao, Yao Yao, Lanqing Li, Wanpeng Zhang, Zhicheng An, Zhong Zhang, Shihui Guo, Li Xiao, Xiaoyu Cao, Dijun Luo

CoRR, 2021

Bias-reduced multi-step hindsight experience replay.

Rui Yang, Jiafei Lyu, Yu Yang, Jiangpeng Yan, Feng Luo, Dijun Luo, Lanqing Li, Xiu Li

CoRR, 2021

Improved Context-Based Offline Meta-RL with Attention and Contrastive Learning.

Lanqing Li, Yuanhao Huang, Dijun Luo

CoRR, 2021

Zeus: Improving Resource Efficiency via Workload Colocation for Massive Kubernetes Clusters.

Xiaolong Zhang, Lanqing Li, Yuan Wang, E. Chen, Lidan Shou

IEEE Access, 2021

FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization.

Lanqing Li, Rui Yang, Dijun Luo

Proceedings of the 9th International Conference on Learning Representations, 2021

A Simulator-based Planning Framework for Optimizing Autonomous Greenhouse Control Strategy.

Zhicheng An, Xiaoyan Cao, Yao Yao, Wanpeng Zhang, Lanqing Li, Yue Wang, Shihui Guo, Dijun Luo

Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, 2021

2020

Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization.

Lanqing Li, Rui Yang, Dijun Luo

CoRR, 2020