Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization. - Lanqing Li; Rui Yang 010; Dijun Luo (CoRR, 2020)

A Simulator-based Planning Framework for Optimizing Autonomous Greenhouse Control Strategy. - Zhicheng An; Xiaoyan Cao; Yao Yao 006; Wanpeng Zhang 002; Lanqing Li; Yue Wang; Shihui Guo; Dijun Luo (ICAPS, 2021)

FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization. - Lanqing Li; Rui Yang; Dijun Luo (ICLR, 2021)

Zeus: Improving Resource Efficiency via Workload Colocation for Massive Kubernetes Clusters. - Xiaolong Zhang 008; Lanqing Li; Yuan Wang 075; E. Chen 002; Lidan Shou (IEEE Access, 2021)

Improved Context-Based Offline Meta-RL with Attention and Contrastive Learning. - Lanqing Li; Yuanhao Huang; Dijun Luo (CoRR, 2021)

Bias-reduced multi-step hindsight experience replay. - Rui Yang 010; Jiafei Lyu; Yu Yang 015; Jiangpeng Yan; Feng Luo; Dijun Luo; Lanqing Li; Xiu Li 001 (CoRR, 2021)

IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control. - Xiaoyan Cao; Yao Yao 006; Lanqing Li; Wanpeng Zhang 002; Zhicheng An; Zhong Zhang; Shihui Guo; Li Xiao 009; Xiaoyu Cao; Dijun Luo (CoRR, 2021)

Local Augmentation for Graph Neural Networks. - Songtao Liu; Hanze Dong; Lanqing Li; Tingyang Xu; Yu Rong 001; Peilin Zhao; Junzhou Huang; Dinghao Wu (CoRR, 2021)

iGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control. - Xiaoyan Cao; Yao Yao 006; Lanqing Li; Wanpeng Zhang 002; Zhicheng An; Zhong Zhang; Li Xiao 009; Shihui Guo; Xiaoyu Cao; Meihong Wu; Dijun Luo (AAAI, 2022)

Local Augmentation for Graph Neural Networks. - Songtao Liu; Rex Ying; Hanze Dong; Lanqing Li; Tingyang Xu; Yu Rong 001; Peilin Zhao; Junzhou Huang; Dinghao Wu (ICML, 2022)

UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup. - Zongbo Han; Zhipeng Liang; Fan Yang 081; Liu Liu 014; Lanqing Li; Yatao Bian; Peilin Zhao; Bingzhe Wu; Changqing Zhang; Jianhua Yao 001 (NeurIPS, 2022)

Value Penalized Q-Learning for Recommender Systems. - Chengqian Gao; Ke Xu; Kuangqi Zhou; Lanqing Li; Xueqian Wang 001; Bo Yuan 008; Peilin Zhao (SIGIR, 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 060; Jiaxiang Wu 001; Bingzhe Wu; Long-Kai Huang; Tingyang Xu; Yu Rong 001; Lanqing Li; Jie Ren; Ding Xue; Houtim Lai; Shaoyong Xu; et al. (CoRR, 2022)

Robust Imitation Learning from Corrupted Demonstrations. - Liu Liu 014; Ziyang Tang; Lanqing Li; Dijun Luo (CoRR, 2022)

ImDrug: A Benchmark for Deep Imbalanced Learning in AI-aided Drug Discovery. - Lanqing Li; Liang Zeng 002; Ziqi Gao; Shen Yuan; Yatao Bian; Bingzhe Wu; Hengtong Zhang; Chan Lu; Yang Yu 010; Wei Liu 005; Hongteng Xu; Jia Li 009; et al. (CoRR, 2022)

ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification. - Liang Zeng 002; Lanqing Li; Ziqi Gao; Peilin Zhao; Jian Li (AAAI, 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 009 (AAAI, 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 060; Jiaxiang Wu 001; Bingzhe Wu; Lanqing Li; Long-Kai Huang; Tingyang Xu; Yu Rong 001; Jie Ren; Ding Xue; Houtim Lai; Wei Liu 005; et al. (AAAI, 2023)

On the Pitfall of Mixup for Uncertainty Calibration. - Deng-Bao Wang; Lanqing Li; Peilin Zhao; Pheng-Ann Heng; Min-Ling Zhang (CVPR, 2023)

Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition. - Zhipeng Zhou; Lanqing Li; Peilin Zhao; Pheng-Ann Heng; Wei Gong 001 (CVPR, 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 (PCCNT, 2023)

Deploying Offline Reinforcement Learning with Human Feedback. - Ziniu Li; Ke Xu; Liu Liu 014; Lanqing Li; Deheng Ye; Peilin Zhao (CoRR, 2023)

Reweighted Mixup for Subpopulation Shift. - Zongbo Han; Zhipeng Liang; Fan Yang 081; Liu Liu 014; Lanqing Li; Yatao Bian; Peilin Zhao; Qinghua Hu; Bingzhe Wu; Changqing Zhang; Jianhua Yao 001 (CoRR, 2023)

MolKD: Distilling Cross-Modal Knowledge in Chemical Reactions for Molecular Property Prediction. - Liang Zeng 002; Lanqing Li; Jian Li (CoRR, 2023)

Towards an Automatic AI Agent for Reaction Condition Recommendation in Chemical Synthesis. - Kexin Chen 003; Junyou Li; Kunyi Wang; Yuyang Du 001; Jiahui Yu; Jiamin Lu; Lanqing Li; Jiezhong Qiu; Qun Fang; Pheng-Ann Heng; Guangyong Chen (CoRR, 2023)

Dynamics Adapted Imitation Learning. - Zixuan Liu 002; Liu Liu 014; Bingzhe Wu; Lanqing Li; Xueqian Wang 001; Bo Yuan 008; Peilin Zhao (Trans. Mach. Learn. Res., 2023)

Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning. - Lanqing Li; Hai Zhang; Xinyu Zhang; Shatong Zhu; Yang Yu; Junqiao Zhao; Pheng-Ann Heng (NeurIPS, 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)

An Autonomous Large Language Model Agent for Chemical Literature Data Mining. - Kexin Chen 003; Hanqun Cao; Junyou Li; Yuyang Du 001; Menghao Guo; Xin Zeng; Lanqing Li; Jiezhong Qiu; Pheng-Ann Heng; Guangyong Chen (CoRR, 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)

Solving the non-submodular network collapse problems via Decision Transformer. - Kaili Ma 001; Han Yang 002; Shanchao Yang; Kangfei Zhao; Lanqing Li; Yongqiang Chen 002; Junzhou Huang; James Cheng; Yu Rong 001 (Neural Networks, 2024)

Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning. - Hai Zhang; Boyuan Zheng; Tianying Ji; Jinhang Liu; Anqi Guo; Junqiao Zhao; Lanqing Li (ICLR, 2025)