论文标题
在最接近的地方寻求分配回归的性能以加倍度量
Performance of Distribution Regression with Doubling Measure under the seek of Closest Point
论文作者
论文摘要
我们研究分布分布的分布分布的分布回归问题大于一个。首先，我们探索任何具有大于一个大于一个的分布的分布的几何形状，并围绕它建立一个小理论。然后，我们展示了如何利用该理论来找到最近的分布之一，并根据这些分布计算回归值。最后，我们在此处提供了建议的方法的准确性，并为其提供了理论分析。
We study the distribution regression problem assuming the distribution of distributions has a doubling measure larger than one. First, we explore the geometry of any distributions that has doubling measure larger than one and build a small theory around it. Then, we show how to utilize this theory to find one of the nearest distributions adaptively and compute the regression value based on these distributions. Finally, we provide the accuracy of the suggested method here and provide the theoretical analysis for it.
