Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease.

ABSTRACT: Consider samples from two different data sources [Formula: see text] and [Formula: see text]. We only observe their transformed versions [Formula: see text] and [Formula: see text], for some known function class h(·) and g(·). Our goal is to perform a statistical test checking if P_source = P_target while removing the distortions induced by the transformations. This problem is closely related to domain adaptation, and in our case, is motivated by the need to combine clinical and imaging based biomarkers from multiple sites and/or batches - a fairly common impediment in conducting analyses with much larger sample sizes. We address this problem using ideas from hypothesis testing on the transformed measurements, wherein the distortions need to

SUBMITTER: Zhou HH 

PROVIDER: S-EPMC5754041 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature