Research

Publications:

  1. M. Egger, R. Bitar, A. Wachter-Zeh and D. Gündüz, "Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits," submitted to IEEE Journal on Selected Areas in Communications (JSAC), 2022.

  2. M. Xhemrishi, M. Egger and R. Bitar, "Efficient Private Storage of Sparse Machine Learning Data," IEEE Information Theory Workshop (ITW), 2022.

  3. M. Egger, R. Bitar, A. Wachter-Zeh and D. Gündüz, "Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits," IEEE International Symposium on Information Theory (ISIT), 2022.

  4. M. Egger, T. Schamberger, L. Tebelmann, F. Lippert, G. Sigl "A Second Look at the ASCAD Databases," International Workshop on Constructive Side-Channel Analysis and Secure Design (COSADE), 2022.

Public Talks:

  • "Challenges in Federated Learning - A Brief Overview," contributed talk at TUM ICE Workshop, August 2022.

  • "Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits," conference talk at International Symposium on Information Theory (ISIT), June 2022.

  • "Exploring While Exploiting Workers for Efficient Distributed Machine Learning," master thesis final presentation at TUM, February 2022.

  • "An IoT-Gateway for Cloud-Based Asset Tracking via Bluetooth Low Energy - Strategic Decisions and Development Steps Towards Prototyping," invited talk organized by VDE, June 2021.