On The Convergence And Robustness Of Adversarial Training
Adversarial training has emerged as a fundamental technique for improving the robustness of machine learning models against adversarial attacks. In recent years, as neural networks and other predictive models have grown increasingly complex, researchers and practitioners have discovered that small, carefully crafted perturbations to input data can lead to significant misclassifications. Adversarial training seeks to … Read more