Selective Classification Via Neural Network Training Dynamics

no code implementations • 26 May 2022 • Stephan Rabanser, Anvith Thudi, Kimia Hamidieh, Adam Dziedzic, Nicolas Papernot

Selective classification is the task of rejecting inputs a model would predict incorrectly on through a trade-off between input space coverage and model accuracy.

Classification

The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations

no code implementations • 6 May 2022 • Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi

Across two different blackbox model architectures and four popular explainability methods, we find that the approximation quality of explanation models, also known as the fidelity, differs significantly between subgroups.

BIG-bench Machine Learning Fairness

Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning

no code implementations • ICLR 2022 • Natalie Dullerud, Karsten Roth, Kimia Hamidieh, Nicolas Papernot, Marzyeh Ghassemi

Deep metric learning (DML) enables learning with less supervision through its emphasis on the similarity structure of representations.

Attribute Fairness +2