June 11, 2024, 4:48 a.m. | Donggeun Ko, Sangwoo Jo, Dongjun Lee, Namjun Park, Jaekwang Kim

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.06134v1 Announce Type: cross
Abstract: Dataset bias is a significant challenge in machine learning, where specific attributes, such as texture or color of the images are unintentionally learned resulting in detrimental performance. To address this, previous efforts have focused on debiasing models either by developing novel debiasing algorithms or by generating synthetic data to mitigate the prevalent dataset biases. However, generative approaches to date have largely relied on using bias-specific samples from the dataset, which are typically too scarce. In …

abstract algorithms arxiv attributes bias challenge color cs.ai cs.cv cs.lg data data generation dataset diffusion images machine machine learning novel performance style synthetic synthetic data texture type via

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