Long-Tailed Classification by Keeping the Good and …

Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect Kaihua Tang1 , Jianqiang Huang1,2 , Hanwang Zhang1. 1. Nanyang Technological University, 2 Damo Academy, Alibaba Group Abstract As the class size grows, maintaining a balanced dataset across many classes is challenging because the data are Long-Tailed in nature; it is even impossible when the sample-of-interest co-exists with each other in one collectable unit, , multiple visual instances in one image. Therefore, Long-Tailed classification is the key to deep learning at scale. However, existing methods are mainly based on re- weighting/re-sampling heuristics that lack a fundamental theory.

Causal Inference. Causal inference [23, 35] has been widely adopted in psychology, politics and epidemiology for years [36, 37, 38]. It doesn’t just serve as an interpretation framework, but also provides solutions to achieve the desired objectives by pursing causal effect. Recently, causal

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  Inference, Casual, Causal inference

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