Comparing Apples to Oranges: Learning Similarity Functions for Data Produced by Different Distributions. (arXiv:2208.12731v1 [cs.LG])

Similarity functions measure how comparable pairs of elements are, and play a
key role in a wide variety of applications, e.g., Clustering problems and
considerations of Individual Fairness. However, access to an accurate
similarity function should not always be considered guaranteed. Specifically,
when the elements to be compared are produced by different distributions, or in
other words belong to different ``demographic'' groups, knowledge of their true
similarity might be very difficult to obtain. In this work, we present a
sampling …

arxiv data learning lg