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Yi Ma
Yi Ma
Verified email at tju.edu.cn - Homepage
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Cited by
Year
Spectral-based graph convolutional network for directed graphs
Y Ma, J Hao, Y Yang, H Li, J Jin, G Chen
arXiv preprint arXiv:1907.08990, 2019
622019
A hierarchical reinforcement learning based optimization framework for large-scale dynamic pickup and delivery problems
Y Ma, X Hao, J Hao, J Lu, X Liu, T Xialiang, M Yuan, Z Li, J Tang, Z Meng
Advances in Neural Information Processing Systems 34, 23609-23620, 2021
472021
KoGuN: accelerating deep reinforcement learning via integrating human suboptimal knowledge
P Zhang, J Hao, W Wang, H Tang, Y Ma, Y Duan, Y Zheng
arXiv preprint arXiv:2002.07418, 2020
292020
Combining sequence and network information to enhance protein–protein interaction prediction
L Liu, X Zhu, Y Ma, H Piao, Y Yang, X Hao, Y Fu, L Wang, J Peng
BMC bioinformatics 21 (16), 1-13, 2020
272020
A multi-graph attributed reinforcement learning based optimization algorithm for large-scale hybrid flow shop scheduling problem
F Ni, J Hao, J Lu, X Tong, M Yuan, J Duan, Y Ma, K He
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
252021
Dynamic knapsack optimization towards efficient multi-channel sequential advertising
X Hao, Z Peng, Y Ma, G Wang, J Jin, J Hao, S Chen, R Bai, M Xie, M Xu, ...
International Conference on Machine Learning, 4060-4070, 2020
172020
Large scale deep reinforcement learning in war-games
H Wang, H Tang, J Hao, X Hao, Y Fu, Y Ma
2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020
92020
Integrating sequence and network information to enhance protein-protein interaction prediction using graph convolutional networks
L Liu, Y Ma, X Zhu, Y Yang, X Hao, L Wang, J Peng
2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2019
92019
Machine Learning Enabled Quickly Predicting of Detonation Properties of N‐Containing Molecules for Discovering New Energetic Materials
F Hou, Y Ma, Z Hu, S Ding, H Fu, L Wang, X Zhang, G Li
Advanced Theory and Simulations 4 (6), 2100057, 2021
72021
Pandr: Fast adaptation to new environments from offline experiences via decoupling policy and environment representations
T Sang, H Tang, Y Ma, J Hao, Y Zheng, Z Meng, B Li, Z Wang
arXiv preprint arXiv:2204.02877, 2022
52022
Ensemble-based Offline-to-Online Reinforcement Learning: From Pessimistic Learning to Optimistic Exploration
K Zhao, Y Ma, J Liu, Y Zheng, Z Meng
arXiv preprint arXiv:2306.06871, 2023
32023
SplitNet: a reinforcement learning based sequence splitting method for the MinMax multiple travelling salesman problem
H Liang, Y Ma, Z Cao, T Liu, F Ni, Z Li, J Hao
Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8720-8727, 2023
12023
State-Aware Proximal Pessimistic Algorithms for Offline Reinforcement Learning
C Chen, H Tang, Y Ma, C Wang, Q Shen, D Li, J Hao
arXiv preprint arXiv:2211.15065, 2022
12022
Reining Generalization in Offline Reinforcement Learning via Representation Distinction
Y Ma, H Tang, D Li, Z Meng
Advances in Neural Information Processing Systems 36, 2024
2024
OSCAR: OOD State-Conservative Offline Reinforcement Learning for Sequential Decision Making
Y Ma, C Wang, C Chen, J Liu, Z Meng, Y Zheng, J Hao
CAAI Artificial Intelligence Research 2, 2023
2023
A Hierarchical Imitation Learning-based Decision Framework for Autonomous Driving
H Liang, Z Dong, Y Ma, X Hao, Y Zheng, J Hao
Proceedings of the 32nd ACM International Conference on Information and …, 2023
2023
Rethinking Decision Transformer via Hierarchical Reinforcement Learning
Y Ma, C Xiao, H Liang, HAO Jianye
2023
Driving SMARTS Competition at NeurIPS 2022: Insights and Outcome
A Rasouli, S Alizadeh, I Kotseruba, Y Ma, H Liang, Y Tian, Z Huang, H Liu, ...
NeurIPS 2022 Competition Track, 73-84, 2023
2023
Improving Offline-to-Online Reinforcement Learning with Q-Ensembles
K Zhao, Y Ma, J Liu, HAO Jianye, Y Zheng, Z Meng
ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023
2023
A Policy-Decoupled Method for High-Quality Data Augmentation in Offline Reinforcement Learning
S Lian, Y Ma, J Liu, HAO Jianye, Y Zheng, Z Meng
ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023
2023
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