【论文精读】Learning Bounds for Importance Weighting
Learning Bounds for Importance Weighting 原论文地址：Learning Bounds for Importance Weighting Abstract 1 Introduction 现实世界中机器学习训练数据和测试数据样本的分布会有偏差。一个常见的修正方法叫做importance weighting，它通过给不同的训练样本的带价值赋予权重来平衡这种偏差。一
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相关文章
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