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[D] What is a SOTA of imbalanced learning?

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.

submitted by /u/vaseline555
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.