Protecting Student Data in ML Pipelines: An Overview of Privacy-Preserving ML

Johannes Schleiss, Kolja Günther, Sebastian Stober. Protecting Student Data in ML Pipelines: An Overview of Privacy-Preserving ML. In Maria Mercedes Rodrigo, Noburu Matsuda, Alexandra I. Cristea, Vania Dimitrova, editors, Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners' and Doctoral Consortium - 23rd International Conference, AIED 2022, Durham, UK, July 27-31, 2022, Proceedings, Part II. Volume 13356 of Lecture Notes in Computer Science, pages 532-536, Springer, 2022. [doi]

Abstract

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