NeurIPS 2019poster11 citations
The Label Complexity of Active Learning from Observational Data
Songbai Yan, Kamalika Chaudhuri, Tara Javidi
Abstract
Counterfactual learning from observational data involves learning a classifier on an entire population based on data that is observed conditioned on a selection policy. This work considers this problem in an active setting, where the learner additionally has access to unlabeled examples and can choose to get a subset of these labeled by an oracle.
BibTeX
@inproceedings{NEURIPS2019_1019c809,
author = {Yan, Songbai and Chaudhuri, Kamalika and Javidi, Tara},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {The Label Complexity of Active Learning from Observational Data},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/1019c8091693ef5c5f55970346633f92-Paper.pdf},
volume = {32},
year = {2019}
}