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FARM: A Fairness-Aware Recommendation Method for High Visibility and Low Visibility Mobile APPs.

, , , and . IEEE Access, (2020)

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FARM: A Fairness-Aware Recommendation Method for High Visibility and Low Visibility Mobile APPs., , , and . IEEE Access, (2020)Corrigendum to Ä Survey on Vehicular Edge Computing: Architecture, Applications, Technical Issues, and Future Directions"., , , and . Wirel. Commun. Mob. Comput., (2019)Security and Cost-Aware Computation Offloading via Deep Reinforcement Learning in Mobile Edge Computing., , , , , , and . Wirel. Commun. Mob. Comput., (2019)EdgeMoE: Fast On-Device Inference of MoE-based Large Language Models., , , , , and . CoRR, (2023)Federated NLP in Few-shot Scenarios., , , , and . CoRR, (2022)Accelerating Vertical Federated Learning., , , , , , and . CoRR, (2022)Automatic Road Extraction with Multi-Source Data Revisited: Completeness, Smoothness and Discrimination., , , and . Proc. VLDB Endow., 16 (11): 3004-3017 (2023)A cooperative route choice approach via virtual vehicle in IoV., , , and . Veh. Commun., (2017)Reinforcement learning-enabled efficient data gathering in underground wireless sensor networks., , , , and . Pers. Ubiquitous Comput., 27 (3): 581-598 (2023)AOM: adaptive mobile data traffic offloading for M2M networks., , , and . Pers. Ubiquitous Comput., 20 (6): 863-873 (2016)