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- W4292387165 abstract "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." @default.
- W4292387165 created "2022-08-20" @default.
- W4292387165 creator A5068792494 @default.
- W4292387165 date "2022-03-01" @default.
- W4292387165 modified "2023-09-27" @default.
- W4292387165 title "Nearest Neighbor outperforms Kernel-Kernel Methods for Distribution Regression" @default.
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- W4292387165 doi "https://doi.org/10.1109/cacml55074.2022.00009" @default.
- W4292387165 hasPublicationYear "2022" @default.
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