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ORCIDMaximilian Egger
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2020 – today
- 2024
[j1]Rawad Bitar
, Maximilian Egger, Antonia Wachter-Zeh, Marvin Xhemrishi:
Sparsity and Privacy in Secret Sharing: A Fundamental Trade-Off. IEEE Trans. Inf. Forensics Secur. 19: 5136-5150 (2024)- [c9]Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz, Nir Weinberger:
Capacity-Maximizing Input Symbol Selection for Discrete Memoryless Channels. ISIT 2024: 723-728 - [i14]Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz, Nir Weinberger:
Maximal-Capacity Discrete Memoryless Channel Identification. CoRR abs/2401.10204 (2024) - [i13]Yue Xia, Christoph Hofmeister, Maximilian Egger, Rawad Bitar:
Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises. CoRR abs/2405.08698 (2024) - [i12]Yue Xia, Christoph Hofmeister, Maximilian Egger, Rawad Bitar:
LoByITFL: Low Communication Secure and Private Federated Learning. CoRR abs/2405.19217 (2024) - [i11]Afonso de Sá Delgado Neto, Maximilian Egger, Mayank Bakshi, Rawad Bitar:
Communication-Efficient Byzantine-Resilient Federated Zero-Order Optimization. CoRR abs/2406.14362 (2024) - [i10]Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz, Nir Weinberger:
Capacity-Maximizing Input Symbol Selection for Discrete Memoryless Channels. CoRR abs/2407.01263 (2024) - [i9]Maximilian Egger, Ghadir Ayache, Rawad Bitar, Antonia Wachter-Zeh, Salim El Rouayheb:
Self-Duplicating Random Walks for Resilient Decentralized Learning on Graphs. CoRR abs/2407.11762 (2024) - [i8]Maximilian Egger, Christoph Hofmeister, Cem Kaya, Rawad Bitar, Antonia Wachter-Zeh:
Scalable and Reliable Over-the-Air Federated Edge Learning. CoRR abs/2407.11807 (2024) - 2023
- [c8]Thomas Schamberger, Maximilian Egger, Lars Tebelmann:
Hide and Seek: Using Occlusion Techniques for Side-Channel Leakage Attribution in CNNs - An Evaluation of the ASCAD Databases. ACNS Workshops 2023: 139-158 - [c7]Maximilian Egger, Christoph Hofmeister, Antonia Wachter-Zeh, Rawad Bitar:
Private Aggregation in Wireless Federated Learning with Heterogeneous Clusters. ISIT 2023: 54-59 - [c6]Maximilian Egger, Serge Kas Hanna, Rawad Bitar:
Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load. ISIT 2023: 1336-1341 - [c5]Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz, Nir Weinberger:
Maximal-Capacity Discrete Memoryless Channel Identification. ISIT 2023: 2248-2253 - [c4]Maximilian Egger, Marvin Xhemrishi, Antonia Wachter-Zeh, Rawad Bitar:
Sparse and Private Distributed Matrix Multiplication with Straggler Tolerance. ISIT 2023: 2535-2540 - [i7]Maximilian Egger, Serge Kas Hanna, Rawad Bitar:
Fast and Straggler-Tolerant Distributed SGD with Reduced Computation Load. CoRR abs/2304.08589 (2023) - [i6]Maximilian Egger, Christoph Hofmeister, Antonia Wachter-Zeh, Rawad Bitar:
Private Aggregation in Wireless Federated Learning with Heterogeneous Clusters. CoRR abs/2306.14088 (2023) - [i5]Maximilian Egger, Marvin Xhemrishi, Antonia Wachter-Zeh, Rawad Bitar:
Sparse and Private Distributed Matrix Multiplication with Straggler Tolerance. CoRR abs/2306.15134 (2023) - [i4]Rawad Bitar, Maximilian Egger, Antonia Wachter-Zeh, Marvin Xhemrishi:
Sparsity and Privacy in Secret Sharing: A Fundamental Trade-Off. CoRR abs/2308.06413 (2023) - 2022
- [c3]Maximilian Egger, Thomas Schamberger, Lars Tebelmann, Florian Lippert, Georg Sigl:
A Second Look at the ASCAD Databases. COSADE 2022: 75-99 - [c2]Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz:
Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits. ISIT 2022: 1653-1658 - [c1]Marvin Xhemrishi, Maximilian Egger, Rawad Bitar:
Efficient Private Storage of Sparse Machine Learning Data. ITW 2022: 214-219 - [i3]Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz:
Efficient Distributed Machine Learning via Combinatorial Multi-Armed Bandits. CoRR abs/2202.08302 (2022) - [i2]Marvin Xhemrishi, Maximilian Egger, Rawad Bitar:
Efficient Private Storage of Sparse Machine Learning Data. CoRR abs/2206.06676 (2022) - [i1]Luis Maßny, Christoph Hofmeister, Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh:
Nested Gradient Codes for Straggler Mitigation in Distributed Machine Learning. CoRR abs/2212.08580 (2022)
Coauthor Index
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