Cover Image

Perfect Privacy for Discriminator-Based Byzantine-Resilient Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xia, Yue, Hofmeister, Christoph, Egger, Maximilian, Bitar, Rawad
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Distributed, Parallel, and Cluster Computing Information Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Byzantine-Resilient Secure Aggregation for Federated Learning Without Privacy Compromises
by: Xia, Yue, et al.
Published: (2024)

Private Aggregation for Byzantine-Resilient Heterogeneous Federated Learning
by: Egger, Maximilian, et al.
Published: (2025)

LoByITFL: Low Communication Secure and Private Federated Learning
by: Xia, Yue, et al.
Published: (2024)

Scalable and Reliable Over-the-Air Federated Edge Learning
by: Egger, Maximilian, et al.
Published: (2024)

Federated One-Shot Learning with Data Privacy and Objective-Hiding
by: Egger, Maximilian, et al.
Published: (2025)

Byzantine-Resilient Zero-Order Optimization for Communication-Efficient Heterogeneous Federated Learning
by: Egger, Maximilian, et al.
Published: (2025)

Interactive Byzantine-Resilient Gradient Coding for General Data Assignments
by: Jain, Shreyas, et al.
Published: (2024)

Beyond Trade-offs: A Unified Framework for Privacy, Robustness, and Communication Efficiency in Federated Learning
by: Xia, Yue, et al.
Published: (2025)

BICompFL: Stochastic Federated Learning with Bi-Directional Compression
by: Egger, Maximilian, et al.
Published: (2025)

Private Aggregation in Hierarchical Wireless Federated Learning with Partial and Full Collusion
by: Egger, Maximilian, et al.
Published: (2023)

Self-Regulating Random Walks for Resilient Decentralized Learning on Graphs
by: Egger, Maximilian, et al.
Published: (2024)

Source Anonymity for Private Random Walk Decentralized Learning
by: Egger, Maximilian, et al.
Published: (2025)

ProDiGy: Proximity- and Dissimilarity-Based Byzantine-Robust Federated Learning
by: Ergisi, Sena, et al.
Published: (2025)

On the Extension of Private Distributed Matrix Multiplication Schemes to the Grid Partition
by: Hofmeister, Christoph, et al.
Published: (2026)

On the Byzantine-Resilience of Distillation-Based Federated Learning
by: Roux, Christophe, et al.
Published: (2024)

Brave: Byzantine-Resilient and Privacy-Preserving Peer-to-Peer Federated Learning
by: Xu, Zhangchen, et al.
Published: (2024)

ByzSecAgg: A Byzantine-Resistant Secure Aggregation Scheme for Federated Learning Based on Coded Computing and Vector Commitment
by: Jahani-Nezhad, Tayyebeh, et al.
Published: (2023)

Privacy-aware Berrut Approximated Coded Computing for Federated Learning
by: Luaña, Xavier Martínez, et al.
Published: (2024)

Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework
by: Moradi, Parsa, et al.
Published: (2024)

Byzantine-Resilient Distributed Computation via Task Replication and Local Computations
by: Rajesh, Aayush, et al.
Published: (2025)

Automated Byzantine-Resilient Clustered Decentralized Federated Learning for Battery Intelligence in Connected EVs
by: Bouchiha, Mouhamed Amine, et al.
Published: (2026)

CAFe: Cost and Age aware Federated Learning
by: Liyanaarachchi, Sahan, et al.
Published: (2024)

Decentralized Federated Learning Over Imperfect Communication Channels
by: Li, Weicai, et al.
Published: (2024)

Closing the Generalization Gap in Parameter-efficient Federated Edge Learning
by: Du, Xinnong, et al.
Published: (2025)

Personalized Federated Learning for Generative AI-Assisted Semantic Communications
by: Peng, Yubo, et al.
Published: (2024)

Hierarchical Federated Learning with SignSGD: A Highly Communication-Efficient Approach
by: Kazemi, Amirreza, et al.
Published: (2026)

Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2026)

Approximate Gradient Coding for Privacy-Flexible Federated Learning with Non-IID Data
by: Makkonen, Okko, et al.
Published: (2024)

No Vandalism: Privacy-Preserving and Byzantine-Robust Federated Learning
by: Xing, Zhibo, et al.
Published: (2024)

Centroid Approximation for Byzantine-Tolerant Federated Learning
by: Cambus, Mélanie, et al.
Published: (2025)

NeRCC: Nested-Regression Coded Computing for Resilient Distributed Prediction Serving Systems
by: Moradi, Parsa, et al.
Published: (2024)

Practical Framework for Privacy-Preserving and Byzantine-robust Federated Learning
by: Zhang, Baolei, et al.
Published: (2025)

SketchGuard: Scaling Byzantine-Robust Decentralized Federated Learning via Sketch-Based Screening
by: Rangwala, Murtaza, et al.
Published: (2025)

Generalization Error Analysis for Attack-Free and Byzantine-Resilient Decentralized Learning with Data Heterogeneity
by: Ye, Haoxiang, et al.
Published: (2025)

Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers
by: Dorfman, Ron, et al.
Published: (2024)

Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation
by: Xu, Jiahao, et al.
Published: (2024)

The Entrapment Problem in Random Walk Decentralized Learning
by: Liu, Zonghong, et al.
Published: (2024)

Learning from Acceptance: Cumulative Regret in the Game of Coding
by: Nodehi, Hanzaleh Akbari, et al.
Published: (2026)

Over-the-Air Multi-Sensor Inference with Neural Networks Using Memristor-Based Analog Computing
by: Tegin, Busra, et al.
Published: (2025)

Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm
by: Lyu, Zhonghao, et al.
Published: (2024)