# Meta-Learning for Relative Density-Ratio Estimation

@inproceedings{Kumagai2021MetaLearningFR, title={Meta-Learning for Relative Density-Ratio Estimation}, author={Atsutoshi Kumagai and Tomoharu Iwata and Yasuhiro Fujiwara}, booktitle={NeurIPS}, year={2021} }

The ratio of two probability densities, called a density-ratio, is a vital quantity in machine learning. In particular, a relative density-ratio, which is a bounded extension of the density-ratio, has received much attention due to its stability and has been used in various applications such as outlier detection and dataset comparison. Existing methods for (relative) density-ratio estimation (DRE) require many instances from both densities. However, sufficient instances are often unavailable in…

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