14-820 Special Topics:

12 units, Carnegie Mellon University

This course will provide an introduction to deep learning methods with emphasis on understanding and improving their security, privacy, and fairness properties. The course will cover basics of machine learning and introduce popular deep learning methods. It will delve into applications of deep learning methods in security, their susceptibility to adversarial manipulation, and techniques for making deep learning robust to adversarial manipulation. It will cover stateoftheart methods for explaining blackbox deep learning models to enhance their transparency. It will also examine methods for deep learning that are designed to respect individual privacy and fairness. Students will do homework assignments, critique weekly readings, and complete a course project on a topic of their choice. Prior knowledge of machine learning, deep learning, and security concepts are useful but not required.

Prerequisites: none listed

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