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A Machine Learning Approach to 5G Infrastructure Market Optimization., , , , and . IEEE Trans. Mob. Comput., 19 (3): 498-512 (2020)Optimising 5G infrastructure markets: The business of network slicing., , , , , and . INFOCOM, page 1-9. IEEE, (2017)Toward the network of the future: From enabling technologies to 5G concepts., , , , and . Trans. Emerg. Telecommun. Technol., (2017)CARES: Computation-Aware Scheduling in Virtualized Radio Access Networks., , , , and . IEEE Trans. Wirel. Commun., 17 (12): 7993-8006 (2018)AI-Based Autonomous Control, Management, and Orchestration in 5G: From Standards to Algorithms., , , , , and . IEEE Netw., 34 (6): 14-20 (2020)DeepCog: Cognitive Network Management in Sliced 5G Networks with Deep Learning., , , , and . INFOCOM, page 280-288. IEEE, (2019)Network Slicing Meets Artificial Intelligence: An AI-Based Framework for Slice Management., , , , , and . IEEE Commun. Mag., 58 (6): 32-38 (2020)Digital Twins for Next-Generation Mobile Networks: Applications and Solutions., , , , and . IEEE Commun. Mag., 61 (11): 80-86 (November 2023)$\alpha$-OMC: Cost-Aware Deep Learning for Mobile Network Resource Orchestration., , , , and . INFOCOM Workshops, page 423-428. IEEE, (2019)Mobile traffic forecasting for maximizing 5G network slicing resource utilization., , , , , and . INFOCOM, page 1-9. IEEE, (2017)