Fairness and Robustness in Invariant Learning: A Case Study in Toxicity Classification

1 code implementation • 12 Nov 2020 • Robert Adragna, Elliot Creager, David Madras, Richard Zemel

Robustness is of central importance in machine learning and has given rise to the fields of domain generalization and invariant learning, which are concerned with improving performance on a test distribution distinct from but related to the training distribution.

BIG-bench Machine Learning Causal Discovery +3