Adversarial Robustness

Browse all content tagged with Adversarial Robustness

Glossary

Model Robustness

Model robustness refers to the ability of a machine learning (ML) model to maintain consistent and accurate performance despite variations and uncertainties in the input data. Robust models are crucial for reliable AI applications, ensuring resilience against noise, outliers, distribution shifts, and adversarial attacks.

AI Machine Learning Model Robustness +3
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