The following publications are possibly variants of this publication:
- Adversarial robustness of deep neural networks: A survey from a formal verification perspectiveMeng, Mark Huasong, Bai, Guangdong, Teo, Sin Gee, Hou, Zhe, Xiao, Yan, Lin, Yun, Dong, Jin Song. IEEE Transactions on Dependable and Secure Computing, , 2022.
- Deep Reinforcement Learning for Computation Offloading and Caching in Fog-Based Vehicular NetworksDapeng Lan, Amir Taherkordi, Frank Eliassen, Lei Liu. mass 2020: 622-630 [doi]
- Deep Reinforcement Learning-Based Computation Offloading in Vehicular Edge ComputingWenhan Zhan, Chunbo Luo, Jin Wang, Geyong Min, Hancong Duan. globecom 2019: 1-6 [doi]
- Deep-Reinforcement-Learning-Based Distributed Computation Offloading in Vehicular Edge Computing NetworksLiwei Geng, Hongbo Zhao, Jiayue Wang, Aryan Kaushik, Shuai Yuan, Wenquan Feng. iotj, 10(14):12416-12433, July 2023. [doi]
- Asynchronous Federated Deep Reinforcement Learning-Based URLLC-Aware Computation Offloading in Space-Assisted Vehicular NetworksChao Pan 0002, Zhao Wang, Haijun Liao, Zhenyu Zhou, Xiaoyan Wang 0003, Muhammad Tariq, Sattam Al Otaibi. tits, 24(7):7377-7389, 2023. [doi]
- Multi-Agent Deep Reinforcement Learning based Collaborative Computation Offloading in Vehicular Edge NetworksHao Wang, Huan Zhou 0002, Liang Zhao, Xuxun Liu 0001, Victor C. M. Leung. icdcs 2023: 151-156 [doi]
- Multiagent Deep Reinforcement Learning for Vehicular Computation Offloading in IoTXiaoyu Zhu, Yueyi Luo, Anfeng Liu, Md. Zakirul Alam Bhuiyan, Shaobo Zhang. iotj, 8(12):9763-9773, 2021. [doi]