Feb. 15, 2024, 5:43 a.m. | Wenzhong Yan, Juntao Wang, Feng Yin, Yang Tian, Abdelhak M. Zoubir

cs.LG updates on arXiv.org arxiv.org

arXiv:2311.16856v2 Announce Type: replace
Abstract: In recent years, Graph neural networks (GNNs) have emerged as a prominent tool for classification tasks in machine learning. However, their application in regression tasks remains underexplored. To tap the potential of GNNs in regression, this paper integrates GNNs with attention mechanism, a technique that revolutionized sequential learning tasks with its adaptability and robustness, to tackle a challenging nonlinear regression problem: network localization. We first introduce a novel network localization method based on graph convolutional …

abstract application arxiv attention classification cs.lg eess.sp gnns graph graph neural networks localization machine machine learning massive network networks neural networks paper regression robust stat.ml tasks tool type

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