A Second Look at the ASCAD Databases. - Maximilian Egger; Thomas Schamberger; Lars Tebelmann; Florian Lippert; Georg Sigl (COSADE, 2022)

Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits. - Maximilian Egger; Rawad Bitar; Antonia Wachter-Zeh; Deniz Gündüz (ISIT, 2022)

Efficient Private Storage of Sparse Machine Learning Data. - Marvin Xhemrishi; Maximilian Egger; Rawad Bitar (ITW, 2022)

Nested Gradient Codes for Straggler Mitigation in Distributed Machine Learning. - Luis Maßny; Christoph Hofmeister; Maximilian Egger; Rawad Bitar; Antonia Wachter-Zeh (CoRR, 2022)

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 (ACNS Workshops, 2023)

Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load. - Maximilian Egger; Serge Kas Hanna; Rawad Bitar (ISIT, 2023)

Private Aggregation in Wireless Federated Learning with Heterogeneous Clusters. - Maximilian Egger; Christoph Hofmeister; Antonia Wachter-Zeh; Rawad Bitar (ISIT, 2023)

Sparse and Private Distributed Matrix Multiplication with Straggler Tolerance. - Maximilian Egger; Marvin Xhemrishi; Antonia Wachter-Zeh; Rawad Bitar (ISIT, 2023)

Self-Duplicating Random Walks for Resilient Decentralized Learning on Graphs. - Maximilian Egger; Ghadir Ayache; Rawad Bitar; Antonia Wachter-Zeh; Salim El Rouayheb (GLOBECOM, 2024)

Scalable and Reliable Over-the-Air Federated Edge Learning. - Maximilian Egger; Christoph Hofmeister; Cem Kaya; Rawad Bitar; Antonia Wachter-Zeh (GLOBECOM, 2024)

Capacity-Maximizing Input Symbol Selection for Discrete Memoryless Channels. - Maximilian Egger; Rawad Bitar; Antonia Wachter-Zeh; Deniz Gündüz; Nir Weinberger (ISIT, 2024)

Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises. - Yue Xia; Christoph Hofmeister; Maximilian Egger; Rawad Bitar (ITW, 2024)

LoByITFL: Low Communication Secure and Private Federated Learning. - Yue Xia; Christoph Hofmeister; Maximilian Egger; Rawad Bitar (CoRR, 2024)

Communication-Efficient Byzantine-Resilient Federated Zero-Order Optimization. - Afonso de Sá Delgado Neto; Maximilian Egger; Mayank Bakshi; Rawad Bitar (CoRR, 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)

Federated One-Shot Learning With Data Privacy and Objective-Hiding. - Maximilian Egger; Rüdiger L. Urbanke; Rawad Bitar (IEEE Trans. Inf. Forensics Secur., 2025)

Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning. - Maximilian Egger; Mayank Bakshi; Rawad Bitar (CoRR, 2025)

BICompFL: Stochastic Federated Learning with Bi-Directional Compression. - Maximilian Egger; Rawad Bitar; Antonia Wachter-Zeh; Nir Weinberger; Deniz Gündüz (CoRR, 2025)

Maximal-Capacity Discrete Memoryless Channel Identification. - Maximilian Egger; Rawad Bitar; Antonia Wachter-Zeh; Deniz Gündüz; Nir Weinberger (IEEE Trans. Inf. Theory, 2025)

Source Anonymity for Private Random Walk Decentralized Learning. - Maximilian Egger; Svenja Lage; Rawad Bitar; Antonia Wachter-Zeh (CoRR, 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, 2025)

Efficient Machine Unlearning by Model Splitting and Core Sample Selection. - Maximilian Egger; Rawad Bitar; Rüdiger L. Urbanke (CoRR, 2025)

Private Aggregation for Byzantine-Resilient Heterogeneous Federated Learning. - Maximilian Egger; Rawad Bitar (CoRR, 2025)

Perfect Privacy for Discriminator-Based Byzantine-Resilient Federated Learning. - Yue Xia; Christoph Hofmeister; Maximilian Egger; Rawad Bitar (CoRR, 2025)