As machine learning and deep learning models are impacting on real world environments (e.g., ChatGPT), concerns on the trustworthiness of machine-learned models are rising. In this course, we explore whether popular machine-learned models are trustworthy and then study various learning methods to enchant the models to be trustworthy. To this end, we will learn basic knowledge on machine learning theory, uncertainty learning via conformal prediction, adversarial examples/learning, machine unlearning, differentially private learning, fairness in learning, and miscellaneous topics on trustworthy generative AI.
B2 Room 107
Sangdon Park
Byeonggyu Kim (qudrb6989@postech.ac.kr)