← Back to papers

2024 ICML ICML 2024

Evaluating Model Bias Requires Characterizing its Mistakes

Authors

Isabela Albuquerque , Jessica Schrouff , David Warde-Farley , Ali Taylan Cemgil , Sven Gowal , Olivia Wiles

Related papers

Learning Latent Dynamic Robust Representations for World Models 2024

Beyond Individual Input for Deep Anomaly Detection on Tabular Data 2024

Risk Estimation in a Markov Cost Process: Lower and Upper Bounds 2024

Collapse-Aware Triplet Decoupling for Adversarially Robust Image Retrieval 2024

Ranking-based Client Imitation Selection for Efficient Federated Learning 2024