spectral
Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning Fangchen Y u
These techniques calibrate an initial non-metric distance matrix estimated on incomplete data to a distance metric.
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title
For instance, data augmentation consistency regularization [Sohn et al., 2020, Berthelot et al., 2019] generates pseudo-labels from the current model predictions on
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Conditional Structure Generation through Graph Variational Generative Adversarial Nets
Carl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, Pan Li
Graph embedding has been intensively studied recently, due to the advance of various neural networkmodels.
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Spectral Modification of Graphs for Improved Spectral Clustering
But spectral clustering remains a frequently used baseline, and a serious contender to state-of-the-art graphembeddingmethods,e.g.[20,11,28,22].
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