Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning

24 Aug 2019Vishwali MhasawadeNabeel Abdur RehmanRumi Chunara

While machine learning is rapidly being developed and deployed in health settings such as influenza prediction, there are critical challenges in using data from one environment in another due to variability in features; even within disease labels there can be differences (e.g. "fever" may mean something different reported in a doctor's office versus in an online app). Moreover, models are often built on passive, observational data which contain different distributions of population subgroups (e.g. men or women)... (read more)

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