| Power control based on deep reinforcement learning for spectrum sharing H Zhang, N Yang, W Huangfu, K Long, VCM Leung IEEE Transactions on Wireless Communications 19 (6), 4209-4219, 2020 | 159 | 2020 |
| Secure communications in NOMA system: Subcarrier assignment and power allocation H Zhang, N Yang, K Long, M Pan, GK Karagiannidis, VCM Leung IEEE Journal on Selected Areas in Communications 36 (7), 1441-1452, 2018 | 145 | 2018 |
| Deep neural network for resource management in NOMA networks N Yang, H Zhang, K Long, HY Hsieh, J Liu IEEE Transactions on Vehicular Technology 69 (1), 876-886, 2019 | 71 | 2019 |
| Token-level Direct Preference Optimization Y Zeng, G Liu, W Ma, N Yang, H Zhang, J Wang Forty-first International Conference on Machine Learning ICML 2024, 2024 | 50 | 2024 |
| A review: machine learning for combinatorial optimization problems in energy areas X Yang, Z Wang, H Zhang, N Ma, N Yang, H Liu, H Zhang, L Yang Algorithms 15 (6), 205, 2022 | 29 | 2022 |
| Partially observable multi-agent deep reinforcement learning for cognitive resource management N Yang, H Zhang, R Berry GLOBECOM 2020-2020 IEEE Global Communications Conference, 1-6, 2020 | 25 | 2020 |
| Energy efficient resource allocation for secure NOMA networks H Zhang, N Yang, K Long, M Pan, GK Karagiannidis, A Nallanathan 2018 IEEE 87th Vehicular Technology Conference (VTC Spring), 1-6, 2018 | 16 | 2018 |
| Learn to flap: Foil non-parametric path planning via deep reinforcement learning ZP Wang, RJ Lin, ZY Zhao, X Chen, PM Guo, N Yang, ZC Wang, DX Fan Journal of Fluid Mechanics 984, A9, 2024 | 11 | 2024 |
| Spectrum management scheme in fog IoT networks N Yang, H Zhang, K Long, C Jiang, Y Yang IEEE Communications Magazine 56 (10), 101-107, 2018 | 10 | 2018 |
| Enhancing efficiency and propulsion in bio-mimetic robotic fish through end-to-end deep reinforcement learning X Cui, B Sun, Y Zhu, N Yang, H Zhang, W Cui, D Fan, J Wang Physics of Fluids 36 (3), 2024 | 7 | 2024 |
| Beyond the edge: An advanced exploration of reinforcement learning for mobile edge computing, its applications, and future research trajectories N Yang, S Chen, H Zhang, R Berry IEEE Communications Surveys & Tutorials, 2024 | 6 | 2024 |
| Multi-objective deep reinforcement learning for mobile edge computing N Yang, J Wen, M Zhang, M Tang 2023 21st international symposium on modeling and optimization in mobile, ad …, 2023 | 5 | 2023 |
| Joint caching and transmission in the mobile edge network: An multi-agent learning approach Q Mi, N Yang, H Zhang, H Zhang, J Wang 2021 IEEE Global Communications Conference (GLOBECOM), 1-6, 2021 | 4 | 2021 |
| Hierarchical Reinforcement Learning for Crude Oil Supply Chain Scheduling N Ma, Z Wang, Z Ba, X Li, N Yang, X Yang, H Zhang Algorithms 16 (7), 354, 2023 | 2 | 2023 |
| Age-minimal Multicast by Graph Attention Reinforcement Learning Y Zhang, G Liao, S Cao, N Yang, N Pappas, M Zhang arXiv preprint arXiv:2404.18084, 2024 | | 2024 |
| Correlated Mean Field Imitation Learning Z Zhao, N Yang, X Yan, H Zhang, J Wang, Y Yang arXiv e-prints, arXiv: 2404.09324, 2024 | | 2024 |
| Minimizing Age of Information for Mobile Edge Computing Systems: A Nested Index Approach S Chen, N Yang, M Zhang, J Wang 2023 21st International Symposium on Modeling and Optimization in Mobile, Ad …, 2023 | | 2023 |
Haijun ZhangProfessor, IEEE Fellow, University of Science and Technology BeijingPreverjeni e-poštni naslov na ustb.edu.cn