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Ultra-Reliable and Low-Latency Vehicular Communication: An Active Learning Approach.

, , , and . IEEE Communications Letters, 24 (2): 367-370 (2020)

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A novel framework for scalable video streaming over multi-channel multi-radio wireless mesh networks., , and . MoVid@MMSys, page 4:1-4:6. ACM, (2016)Extreme URLLC: Vision, Challenges, and Key Enablers., , , , , , and . CoRR, (2020)Vehicular Cooperative Perception Through Action Branching and Federated Reinforcement Learning., , , , and . IEEE Trans. Commun., 70 (2): 891-903 (2022)V2V Cooperative Sensing using Reinforcement Learning with Action Branching., , , and . ICC, page 1-6. IEEE, (2021)Ultra-Reliable and Low-Latency Vehicular Communication: An Active Learning Approach., , , and . IEEE Communications Letters, 24 (2): 367-370 (2020)Ultra-Reliable and Low-Latency Vehicular Communication: An Active Learning Approach., , , and . CoRR, (2019)Vehicular Cooperative Perception Through Action Branching and Federated Reinforcement Learning., , , , and . CoRR, (2020)Cooperative Navigation via Relational Graphs and State Abstraction., , and . IEEE Netw. Lett., 5 (4): 184-188 (December 2023)Optimized Age of Information Tail for Ultra-Reliable Low-Latency Communications in Vehicular Networks., , , , and . CoRR, (2019)Cooperative perception in Vehicular Networks using Multi-Agent Reinforcement Learning., , , and . ACSSC, page 408-412. IEEE, (2020)