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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)Optimized Caching and Spectrum Partitioning for D2D enabled Cellular Systems with Clustered Devices., , , , , and . CoRR, (2020)Learning to Entangle Radio Resources in Vehicular Communications: An Oblivious Game-Theoretic Perspective., , , , and . IEEE Trans. Veh. Technol., 68 (5): 4262-4274 (2019)Statistical Analysis of Self-Organizing Networks With Biased Cell Association and Interference Avoidance., , and . IEEE Trans. Veh. Technol., 62 (5): 1950-1961 (2013)Full duplex communications Guest Editorial., , and . IEEE Commun. Mag., 53 (5): 90 (2015)On the Energy and Communication Efficiency Tradeoffs in Federated and Multi-Task Learning., , , and . PIMRC, page 1431-1437. IEEE, (2022)Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning., , , , , and . VTC Fall, page 1-6. IEEE, (2018)LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning., , , , , , and . WWW, page 3347-3357. ACM, (2022)Cooperative Edge Caching via Federated Deep Reinforcement Learning in Fog-RANs., , , , and . ICC Workshops, page 1-6. IEEE, (2021)