Though it is somewhat absurd to find ‘SOTA’ algorithm in imbalanced learning problem,

(since there exists solutions of a different nature)

are there any good recent papers (2018~) on the “method” of dealing with imbalanced learning?

(I wandered around Google scholar, but there are mostly applications of existing methods on domain-specific problems)

I’ve recognized some generative methods like SMOTE, ADASYN, tons of GAN-based techniques, cost-sensitive approaches, transforming loss functions, learning metrics, and over/under samplings, etc.

Among such categories, or other approaches that I don’t know yet, what is the most generally well-working algorithms? (papers?)

Thank you all, in advance.