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Updated: May 16, 2025

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通过扩散模型进行数据增强,以提高AI公平性

Christina Hastings Blow1, Lijun Qian1, Camille Gibson2

  • 1Prairie View A&M University, Electrical and Computer Engineering, Texas A&M University System, Prairie View, TX, United States.

Frontiers in artificial intelligence
|April 3, 2025
PubMed
概括

使用扩散模型生成的合成数据,特别是表式无序扩散概率模型 (Tab-DDPM),可以提高人工智能 (AI) 在二进制分类任务中的公平性.

关键词:
人工智能公平的公平性其他AIF360AIF360这些数据来自COMPAS数据集.成年人收入数据集成年人收入数据集生成型的人工智能再加重样本的重量进行重新加重.

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