A Survey of Deep Long-Tail Classification Advancements

arXiv:2404.15593v1 Announce Type: new
Abstract: Many data distributions in the real world are hardly uniform. Instead, skewed and long-tailed distributions of various kinds are commonly observed. This poses an interesting problem for machine learning, where most algorithms assume or work well with uniformly distributed data. The problem is further exacerbated by current state-of-the-art deep learning models requiring large volumes of training data. As such, learning from imbalanced data remains a challenging research problem and a problem that must be solved …

abstract algorithms art arxiv classification cs.lg current data distributed distributed data machine machine learning state survey type uniform work world