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ORCIDLanqing Li
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
[j3]Kaili Ma, Han Yang
, Shanchao Yang, Kangfei Zhao, Lanqing Li, Yongqiang Chen, Junzhou Huang, James Cheng, Yu Rong:
Solving the non-submodular network collapse problems via Decision Transformer. Neural Networks 176: 106328 (2024)- [i18]Lanqing Li, Hai Zhang, Xinyu Zhang, Shatong Zhu, Junqiao Zhao, Pheng-Ann Heng:
Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning. CoRR abs/2402.02429 (2024) - [i17]Kexin Chen, Hanqun Cao, Junyou Li, Yuyang Du, Menghao Guo, Xin Zeng, Lanqing Li, Jiezhong Qiu, Pheng-Ann Heng, Guangyong Chen:
An Autonomous Large Language Model Agent for Chemical Literature Data Mining. CoRR abs/2402.12993 (2024) - [i16]Hai Zhang, Boyuan Zheng, Anqi Guo, Tianying Ji, Pheng-Ann Heng, Junqiao Zhao, Lanqing Li:
Scrutinize What We Ignore: Reining Task Representation Shift In Context-Based Offline Meta Reinforcement Learning. CoRR abs/2405.12001 (2024) - 2023
- [j2]Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao:
Dynamics Adapted Imitation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c12]Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Lanqing Li, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li:
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. AAAI 2023: 7651-7659 - [c11]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:
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations. AAAI 2023: 8023-8031 - [c10]Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li:
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. AAAI 2023: 11138-11146 - [c9]Zhipeng Zhou, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Wei Gong:
Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition. CVPR 2023: 3499-3509 - [c8]Deng-Bao Wang, Lanqing Li, Peilin Zhao, Pheng-Ann Heng, Min-Ling Zhang:
On the Pitfall of Mixup for Uncertainty Calibration. CVPR 2023: 7609-7618 - [c7]Yulin Zhao, Chong Sun, Lanqing Li, Yifeng Li, Hang Zhou:
Energy Saving Evaluation Method for Energy Storage Technologies Based on the Intimate Data Method of Machine Learning. PCCNT 2023: 59:1-59:5 - [i15]Ziniu Li, Ke Xu, Liu Liu, Lanqing Li, Deheng Ye, Peilin Zhao:
Deploying Offline Reinforcement Learning with Human Feedback. CoRR abs/2303.07046 (2023) - [i14]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Qinghua Hu, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
Reweighted Mixup for Subpopulation Shift. CoRR abs/2304.04148 (2023) - [i13]Liang Zeng, Lanqing Li, Jian Li:
MolKD: Distilling Cross-Modal Knowledge in Chemical Reactions for Molecular Property Prediction. CoRR abs/2305.01912 (2023) - [i12]Kexin Chen, Junyou Li, Kunyi Wang, Yuyang Du, Jiahui Yu, Jiamin Lu, Lanqing Li, Jiezhong Qiu, Qun Fang, Pheng-Ann Heng, Guangyong Chen:
Towards an Automatic AI Agent for Reaction Condition Recommendation in Chemical Synthesis. CoRR abs/2311.10776 (2023) - 2022
- [c6]Xiaoyan Cao, Yao Yao, Lanqing Li, Wanpeng Zhang, Zhicheng An, Zhong Zhang, Li Xiao, Shihui Guo, Xiaoyu Cao, Meihong Wu, Dijun Luo:
iGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control. AAAI 2022: 11837-11845 - [c5]Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu:
Local Augmentation for Graph Neural Networks. ICML 2022: 14054-14072 - [c4]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. NeurIPS 2022 - [c3]Chengqian Gao, Ke Xu, Kuangqi Zhou, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao:
Value Penalized Q-Learning for Recommender Systems. SIGIR 2022: 2008-2012 - [i11]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:
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations. CoRR abs/2201.09637 (2022) - [i10]Liu Liu, Ziyang Tang, Lanqing Li, Dijun Luo:
Robust Imitation Learning from Corrupted Demonstrations. CoRR abs/2201.12594 (2022) - [i9]Liang Zeng, Lanqing Li, Ziqi Gao, Peilin Zhao, Jian Li:
ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. CoRR abs/2205.11332 (2022) - [i8]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:
ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. CoRR abs/2209.07921 (2022) - [i7]Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu, Changqing Zhang, Jianhua Yao:
UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. CoRR abs/2209.08928 (2022) - [i6]Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Tingyang Xu, Peilin Zhao, Lanqing Li, Fugee Tsung, Jia Li:
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder. CoRR abs/2211.16771 (2022) - 2021
- [j1]Xiaolong Zhang, Lanqing Li, Yuan Wang, E. Chen, Lidan Shou:
Zeus: Improving Resource Efficiency via Workload Colocation for Massive Kubernetes Clusters. IEEE Access 9: 105192-105204 (2021) - [c2]Zhicheng An, Xiaoyan Cao, Yao Yao, Wanpeng Zhang, Lanqing Li, Yue Wang, Shihui Guo, Dijun Luo:
A Simulator-based Planning Framework for Optimizing Autonomous Greenhouse Control Strategy. ICAPS 2021: 436-444 - [c1]Lanqing Li, Rui Yang, Dijun Luo:
FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization. ICLR 2021 - [i5]Lanqing Li, Yuanhao Huang, Dijun Luo:
Improved Context-Based Offline Meta-RL with Attention and Contrastive Learning. CoRR abs/2102.10774 (2021) - [i4]Rui Yang, Jiafei Lyu, Yu Yang, Jiangpeng Yan, Feng Luo, Dijun Luo, Lanqing Li, Xiu Li:
Bias-reduced multi-step hindsight experience replay. CoRR abs/2102.12962 (2021) - [i3]Xiaoyan Cao, Yao Yao, Lanqing Li, Wanpeng Zhang, Zhicheng An, Zhong Zhang, Shihui Guo, Li Xiao, Xiaoyu Cao, Dijun Luo:
IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control. CoRR abs/2107.05464 (2021) - [i2]Songtao Liu, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu:
Local Augmentation for Graph Neural Networks. CoRR abs/2109.03856 (2021) - 2020
- [i1]Lanqing Li, Rui Yang, Dijun Luo:
Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization. CoRR abs/2010.01112 (2020)
Coauthor Index
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