Learning Fairly With Class-Imbalanced Data for Interference Coordination
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DOI: 10.1109/tvt.2021.3080678
Abstract: Deep neural networks (DNNs) have been widely applied for classification tasks in wireless communications such as link scheduling, user association and base station (BS) muting. When training a DNN using datasets with highly-skewed class distribution… read more here.
Keywords: interference coordination; learning fairly; imbalanced data; class ... See more keywords