LTF: A Label Transformation Framework for Correcting Label Shift

By Jiaxian Guo, Mingming Gong, Tongliang Liu, Kun Zhang, Dacheng Tao. 2020

43 citations recorded by the source corpus.

How researchers see this paper

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1. Jiaxian Guo

Citations in the corpus

• Online Continual Learning with Contrastive Vision Transformer (2022, background): “One of the major challenges in research on artificial neural networks is developing the ability to accumulate knowledge over time from a non-stationary data stream [7,29,38].”
• Continual Learning through Retrieval and Imagination (2022, methodology): “Although co-sine normalization has been adopted in other visual problem (Gidaris et al. 2018; Wei et al. 2019; Guo et al. 2020; Qi et al. 2018; Hou et al. 2019), we demonstrate that it can effectively eliminate the imbalance in the magnitude of class embeddings and facilitate continual learning…”
• Continual Learning with Lifelong Vision Transformer (2022, unknown): “Label-based methods [28,77,80–82 ,”