Geometric Machine Learning Over Riemannian Manifolds for Wireless Link Scheduling
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DOI: 10.1109/access.2022.3153324
Abstract: In this paper, we propose two novel geometric machine learning (G-ML) methods for the wireless link scheduling problem in device-to-device (D2D) networks. In dynamic D2D networks (e.g., vehicular networks), obtaining a large number of training… read more here.
Keywords: wireless link; training; machine; geometric machine ... See more keywords