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Found 3 papers, 1 papers with code
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training
Machine learning systems often acquire biases by leveraging undesired features in the data, impacting accuracy variably across different sub-populations.
Do Explanations Explain? Model Knows Best
It is a mystery which input features contribute to a neural network's output.
Towards Deep Learning Models Resistant to Large Perturbations
Adversarial robustness has proven to be a required property of machine learning algorithms.
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