Does cost-sensitive learning beat sampling for classifying rare classes?

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Box drawings for learning with imbalanced data (2014, methodology): “(McCarthy, Zabar, and Weiss 2005).”
Plankton classification on imbalanced large scale database via convolutional neural networks with transfer learning (2016, background): “Numerous approaches have been studied for handling with class-imbalanced data [6, 7, 12] by sampling the largesized data [13, 14] or duplicating the small-size data [15, 16].”
Training and assessing classification rules with imbalanced data (2012, methodology): “Both undersampling and oversampling have known drawbacks (McCarthy et al. 2005).”
Learning from Imbalanced Data (2009, background): “domains [11], [52], [53], cost-sensitive learning is superior to”