This course focuses on a range of quality-issue of AI systems, such as robustness, backdoor-freeness, fairness, privacy and interpretability. What is covered include systematic ways of evaluating whether a given AI system (typically in the form of a neural network) satisfies different quality metrics and how to improve the system’s robustness, backdoor-freeness, fairness, privacy and interpretability.
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