AW-GBGAE: An Adaptive Weighted Graph Autoencoder Based on Granular-Balls for General Data Clustering
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DOI: 10.1109/tpami.2025.3596615
Abstract: In the current scenario, a vast amount of unlabeled high-dimensional data exhibits intrinsic relationships, making it suitable for information extraction through graph-based clustering methods. However, these datasets often lack edge structure information and contain numerous… read more here.
Keywords: autoencoder; gbgae adaptive; adaptive weighted; granular balls ... See more keywords