Maximilian Egger

According to our database, Maximilian Egger authored at least 24 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Perfect Privacy for Discriminator-Based Byzantine-Resilient Federated Learning.

Yue Xia, Christoph Hofmeister, Maximilian Egger, Rawad Bitar

CoRR, June, 2025

Private Aggregation for Byzantine-Resilient Heterogeneous Federated Learning.

Maximilian Egger, Rawad Bitar

CoRR, June, 2025

Efficient Machine Unlearning by Model Splitting and Core Sample Selection.

Maximilian Egger, Rawad Bitar, Rüdiger L. Urbanke

CoRR, May, 2025

Multi-Terminal Remote Generation and Estimation Over a Broadcast Channel With Correlated Priors.

Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Nir Weinberger, Deniz Gündüz

CoRR, May, 2025

Source Anonymity for Private Random Walk Decentralized Learning.

Maximilian Egger, Svenja Lage, Rawad Bitar, Antonia Wachter-Zeh

CoRR, May, 2025

Maximal-Capacity Discrete Memoryless Channel Identification.

Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz, Nir Weinberger

IEEE Trans. Inf. Theory, February, 2025

BICompFL: Stochastic Federated Learning with Bi-Directional Compression.

Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Nir Weinberger, Deniz Gündüz

CoRR, February, 2025

Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning.

Maximilian Egger, Mayank Bakshi, Rawad Bitar

CoRR, February, 2025

Federated One-Shot Learning With Data Privacy and Objective-Hiding.

Maximilian Egger, Rüdiger L. Urbanke, Rawad Bitar

IEEE Trans. Inf. Forensics Secur., 2025

2024

Sparsity and Privacy in Secret Sharing: A Fundamental Trade-Off.

Rawad Bitar, Maximilian Egger, Antonia Wachter-Zeh, Marvin Xhemrishi

IEEE Trans. Inf. Forensics Secur., 2024

Communication-Efficient Byzantine-Resilient Federated Zero-Order Optimization.

Afonso de Sá Delgado Neto, Maximilian Egger, Mayank Bakshi, Rawad Bitar

CoRR, 2024

LoByITFL: Low Communication Secure and Private Federated Learning.

Yue Xia, Christoph Hofmeister, Maximilian Egger, Rawad Bitar

CoRR, 2024

Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises.

Yue Xia, Christoph Hofmeister, Maximilian Egger, Rawad Bitar

Proceedings of the IEEE Information Theory Workshop, 2024

Capacity-Maximizing Input Symbol Selection for Discrete Memoryless Channels.

Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz, Nir Weinberger

Proceedings of the IEEE International Symposium on Information Theory, 2024

Scalable and Reliable Over-the-Air Federated Edge Learning.

Maximilian Egger, Christoph Hofmeister, Cem Kaya, Rawad Bitar, Antonia Wachter-Zeh

Proceedings of the 2024 IEEE Global Communications Conference, 2024

Self-Duplicating Random Walks for Resilient Decentralized Learning on Graphs.

Maximilian Egger, Ghadir Ayache, Rawad Bitar, Antonia Wachter-Zeh, Salim El Rouayheb

Proceedings of the 2024 IEEE Global Communications Conference, 2024

2023

Sparse and Private Distributed Matrix Multiplication with Straggler Tolerance.

Maximilian Egger, Marvin Xhemrishi, Antonia Wachter-Zeh, Rawad Bitar

Proceedings of the IEEE International Symposium on Information Theory, 2023

Private Aggregation in Wireless Federated Learning with Heterogeneous Clusters.

Maximilian Egger, Christoph Hofmeister, Antonia Wachter-Zeh, Rawad Bitar

Proceedings of the IEEE International Symposium on Information Theory, 2023

Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load.

Maximilian Egger, Serge Kas Hanna, Rawad Bitar

Proceedings of the IEEE International Symposium on Information Theory, 2023

Hide and Seek: Using Occlusion Techniques for Side-Channel Leakage Attribution in CNNs - An Evaluation of the ASCAD Databases.

Thomas Schamberger, Maximilian Egger, Lars Tebelmann

Proceedings of the Applied Cryptography and Network Security Workshops, 2023

2022

Nested Gradient Codes for Straggler Mitigation in Distributed Machine Learning.

Luis Maßny, Christoph Hofmeister, Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh

CoRR, 2022

Efficient Private Storage of Sparse Machine Learning Data.

Marvin Xhemrishi, Maximilian Egger, Rawad Bitar

Proceedings of the IEEE Information Theory Workshop, 2022

Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits.

Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz

Proceedings of the IEEE International Symposium on Information Theory, 2022

A Second Look at the ASCAD Databases.

Maximilian Egger, Thomas Schamberger, Lars Tebelmann, Florian Lippert, Georg Sigl

Proceedings of the Constructive Side-Channel Analysis and Secure Design, 2022