IBM’s Approach Towards Preserving Adversarial Robustness of Machine Learning Systems

In the real world, machine learning (ML) procedures can be sensitive to adversarial attacks. Algorithms take numeric vectors as inputs. A malicious attack is when you design information in a certain way to elicit the wrong answer from the model. As a response, there is a need to defend against hacks by identifying vulnerabilities, anticipating […]

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