Web: http://arxiv.org/abs/2209.10428

Sept. 22, 2022, 1:11 a.m. | Dimitrios Michael Manias, Ali Chouman, Abdallah Shami

cs.LG updates on arXiv.org arxiv.org

Data-driven approaches and paradigms have become promising solutions to
efficient network performances through optimization. These approaches focus on
state-of-the-art machine learning techniques that can address the needs of 5G
networks and the networks of tomorrow, such as proactive load balancing. In
contrast to model-based approaches, data-driven approaches do not need accurate
models to tackle the target problem, and their associated architectures provide
a flexibility of available system parameters that improve the feasibility of
learning-based algorithms in mobile wireless networks. The …

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