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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. In this paper, we establish a causal inference framework, which not only unravels the whys of previous methods, but also derives a new principled solution.

34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada. ... = 0:9, where iis ranking from head to tail. (c) The relative change of the performance on the basis of = 0:98 shows that the few-shot tail is more vulnerable to the momentum. ... the dynamic curriculum learning [33] and the transferring memory ...

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  Dynamics, Basis, Neural

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