Alabdulmohsin, Ibrahim; Chiou, Nicole; D’Amour, Alexander; Gretton, Arthur; Koyejo, Sanmi; Kusner, Matt J; Pfohl, Stephen R; ... Tsai, Katherine; + view all Alabdulmohsin, Ibrahim; Chiou, Nicole; D’Amour, Alexander; Gretton, Arthur; Koyejo, Sanmi; Kusner, Matt J; Pfohl, Stephen R; Salaudeen, Olawale; Schrouff, Jessica; Tsai, Katherine; - view fewer (2023) Adapting to Latent Subgroup Shifts via Concepts and Proxies. In: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics. (pp. pp. 9637-9661).

Preview

Text alabdulmohsin23a.pdf - Published Version Download (656kB) | Preview

Abstract

We address the problem of unsupervised domain adaptation when the source domain differs from the target domain because of a shift in the distribution of a latent subgroup. When this subgroup confounds all observed data, neither covariate shift nor label shift assumptions apply. We show that the optimal target predictor can be non-parametrically identified with the help of concept and proxy variables available only in the source domain, and unlabeled data from the target. The identification results are constructive, immediately suggesting an algorithm for estimating the optimal predictor in the target. For continuous observations, when this algorithm becomes impractical, we propose a latent variable model specific to the data generation process at hand. We show how the approach degrades as the size of the shift changes, and verify that it outperforms both covariate and label shift adjustment.

Download activity - last month

Export as XMLJSONCSV

Download activity - last 12 months

Export as CSVXMLJSON

Downloads by country - last 12 months

Export as CSVJSONXML

Archive Staff Only

View Item