2 papers
cs.LG2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund +20
Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the…
cs.LG2018
METCC: METric learning for Confounder Control Making distance matter in high dimensional biological analysis
Kabir Manghnani, Adam Drake, Nathan Wan +1
High-dimensional data acquired from biological experiments such as next generation sequencing are subject to a number of confounding effects. These effects include both technical e…