182 citations · 359 across the 11 of their papers we have counts for
3 papers · 1 filter
Fairness and Robustness in Invariant Learning: A Case Study in Toxicity Classification
Robert Adragna, Elliot Creager, David Madras +1
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 perform…
Environment Inference for Invariant Learning
Elliot Creager, Jörn-Henrik Jacobsen, Richard Zemel
Learning models that gracefully handle distribution shifts is central to research on domain generalization, robust optimization, and fairness. A promising formulation is domain-inv…
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
Martin Mladenov, Elliot Creager, Omer Ben-Porat +3
Most recommender systems (RS) research assumes that a user's utility can be maximized independently of the utility of the other agents (e.g., other users, content providers). In re…