Machine Learning Seminar presentation
Topic: Leveraging Deep Learning-Assisted Attacks against Image Obfuscation via Federated Learning
Speaker: Jimmy Tekli, BMW GROUP, Université de Franche-Comté
Time: Wednesday, 2021.05.19, 10:00 CET
How to join: Please contact Jakub Lengiewicz
Federated learning (FL) has recently gained much attention as a machine learning setting where multiple clients collaborate in solving a machine learning problem under the coordination of a central server/coordinator. Each client’s raw data is stored locally without being exchanged nor transferred to the central server; instead, the model’s parameters are shared/aggregated and used to achieve the learning objective. Throughout this seminar, we first present the FL concept, the Federated Averaging algorithm, the FL client/server architecture along its challenges/limitations and applications. Second, we demonstrate how we employed FL as a collaborative adversarial strategy to leverage deep learning-assisted attacks against obfuscated (e.g. blurred) face images.