A semi-supervised kernel two-sample test integrates unlabeled covariate data to achieve asymptotic normality under the null, higher power than standard kernel tests, and consistency against fixed and local alternatives.
Converting high-dimensional regression to high-dimensional conditional density estimation , volume =
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The first circumgalactic dust reddening measurement from Rubin DP1 data finds A_V proportional to r_perp to the -1.8 power within 120 kpc, consistent with prior SDSS/KiDS/DES results despite 1000x smaller area and fainter foreground sample.
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A Semi-Supervised Kernel Two-Sample Test
A semi-supervised kernel two-sample test integrates unlabeled covariate data to achieve asymptotic normality under the null, higher power than standard kernel tests, and consistency against fixed and local alternatives.
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A First Measurement of Circumgalactic Dust Reddening from Only 4.6 deg$^2$ of the Rubin Observatory's DP1
The first circumgalactic dust reddening measurement from Rubin DP1 data finds A_V proportional to r_perp to the -1.8 power within 120 kpc, consistent with prior SDSS/KiDS/DES results despite 1000x smaller area and fainter foreground sample.