Integrating Sequence and Network Information to Enhance Protein-Protein Interaction Prediction Using Graph Convolutional Networks. - Leilei Liu; Yi Ma 005; Xianglei Zhu; Yaodong Yang 002; Xiaotian Hao; Li Wang; Jiajie Peng (BIBM, 2019)

Spectral-based Graph Convolutional Network for Directed Graphs. - Yi Ma 005; Jianye Hao; Yaodong Yang 002; Han Li 005; Junqi Jin; Guangyong Chen (CoRR, 2019)

Large Scale Deep Reinforcement Learning in War-games. - Hanchao Wang; Hongyao Tang; Jianye Hao; Xiaotian Hao; Yue Fu; Yi Ma 005 (BIBM, 2020)

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising. - Xiaotian Hao; Zhaoqing Peng; Yi Ma 005; Guan Wang; Junqi Jin; Jianye Hao; Shan Chen; Rongquan Bai; Mingzhou Xie; Miao Xu; Zhenzhe Zheng; Chuan Yu; et al. (ICML, 2020)

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising. - Xiaotian Hao; Junqi Jin; Jianye Hao; Jin Li; Weixun Wang; Yi Ma 005; Zhenzhe Zheng; Han Li 005; Jian Xu 015; Kun Gai (IJCAI, 2020)

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge. - Peng Zhang; Jianye Hao; Weixun Wang; Hongyao Tang; Yi Ma 005; Yihai Duan; Yan Zheng 002 (IJCAI, 2020)

Combining sequence and network information to enhance protein-protein interaction prediction. - Leilei Liu; Xianglei Zhu; Yi Ma 005; Haiyin Piao; Yaodong Yang 002; Xiaotian Hao; Yue Fu; Li Wang; Jiajie Peng (BMC Bioinform., 2020)

A Multi-Graph Attributed Reinforcement Learning based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem. - Fei Ni 001; Jianye Hao; Jiawen Lu; Xialiang Tong; Mingxuan Yuan; Jiahui Duan; Yi Ma 005; Kun He 001 (KDD, 2021)

A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems. - Yi Ma 005; Xiaotian Hao; Jianye Hao; Jiawen Lu; Xing Liu; Xialiang Tong; Mingxuan Yuan; Zhigang Li; Jie Tang 001; Zhaopeng Meng (NeurIPS, 2021)

PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations. - Tong Sang; Hongyao Tang; Yi Ma 005; Jianye Hao; Yan Zheng 002; Zhaopeng Meng; Boyan Li; Zhen Wang 004 (IJCAI, 2022)

State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning. - Chen Chen 077; Hongyao Tang; Yi Ma 005; Chao Wang; Qianli Shen; Dong Li 016; Jianye Hao (CoRR, 2022)

SplitNet: A Reinforcement Learning Based Sequence Splitting Method for the MinMax Multiple Travelling Salesman Problem. - Hebin Liang; Yi Ma 005; Zilin Cao; Tianyang Liu; Fei Ni 001; Zhigang Li; Jianye Hao (AAAI, 2023)

A Hierarchical Imitation Learning-based Decision Framework for Autonomous Driving. - Hebin Liang; Zibin Dong; Yi Ma 005; Xiaotian Hao; Yan Zheng 002; Jianye Hao (CIKM, 2023)

Reining Generalization in Offline Reinforcement Learning via Representation Distinction. - Yi Ma 005; Hongyao Tang; Dong Li 016; Zhaopeng Meng (NeurIPS, 2023)

In-Sample Policy Iteration for Offline Reinforcement Learning. - Xiaohan Hu; Yi Ma 005; Chenjun Xiao; Yan Zheng 002; Zhaopeng Meng (CoRR, 2023)

HIPODE: Enhancing Offline Reinforcement Learning with High-Quality Synthetic Data from a Policy-Decoupled Approach. - Shixi Lian; Yi Ma 005; Jinyi Liu 002; Yan Zheng 002; Zhaopeng Meng (CoRR, 2023)

Ensemble-based Offline-to-Online Reinforcement Learning: From Pessimistic Learning to Optimistic Exploration. - Kai Zhao; Yi Ma 005; Jinyi Liu 002; Yan Zheng 002; Zhaopeng Meng (CoRR, 2023)

Prioritized Trajectory Replay: A Replay Memory for Data-driven Reinforcement Learning. - Jinyi Liu 002; Yi Ma 005; Jianye Hao; Yujing Hu; Yan Zheng 002; Tangjie Lv; Changjie Fan (CoRR, 2023)

A Trajectory Perspective on the Role of Data Sampling Techniques in Offline Reinforcement Learning. - Jinyi Liu 002; Yi Ma 005; Jianye Hao; Yujing Hu; Yan Zheng 002; Tangjie Lv; Changjie Fan (AAMAS, 2024)

Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback. - Yifu Yuan; Jianye Hao; Yi Ma 005; Zibin Dong; Hebin Liang; Jinyi Liu 002; Zhixin Feng; Kai Zhao; Yan Zheng 002 (ICLR, 2024)

Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation. - Jiashun Liu; Jianye Hao; Yi Ma 005; Shuyin Xia (ICML, 2024)

Rethinking Decision Transformer via Hierarchical Reinforcement Learning. - Yi Ma 005; Jianye Hao; Hebin Liang; Chenjun Xiao (ICML, 2024)

ENOTO: Improving Offline-to-Online Reinforcement Learning with Q-Ensembles. - Kai Zhao; Jianye Hao; Yi Ma 005; Jinyi Liu 002; Yan Zheng 002; Zhaopeng Meng (IJCAI, 2024)

Iteratively Refined Behavior Regularization for Offline Reinforcement Learning. - Yi Ma 005; Jianye Hao; Xiaohan Hu; Yan Zheng 002; Chenjun Xiao (NeurIPS, 2024)

CleanDiffuser: An Easy-to-use Modularized Library for Diffusion Models in Decision Making. - Zibin Dong; Yifu Yuan; Jianye Hao; Fei Ni 001; Yi Ma 005; Pengyi Li 001; Yan Zheng 002 (NeurIPS, 2024)

Unlock the Intermittent Control Ability of Model Free Reinforcement Learning. - Jiashun Liu; Jianye Hao; Xiaotian Hao; Yi Ma 005; Yan Zheng 002; Yujing Hu; Tangjie Lv (NeurIPS, 2024)

Squeeze the Soaked Sponge: Efficient Off-policy Reinforcement Finetuning for Large Language Model. - Jing Liang; Hongyao Tang; Yi Ma 005; Jinyi Liu 002; Yan Zheng 002; Shuyue Hu; Lei Bai 001; Jianye Hao (CoRR, 2025)

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies. - Yi Ma 005; Hongyao Tang; Chenjun Xiao; Yaodong Yang 001; Wei Wei 018; Jianye Hao; Jiye Liang (CoRR, 2025)