Byzantine-Robust Federated Representation Learning
cs.LG, math.OC
Submitted: 2026-09-29
Updated: 2026-09-29
Code: https://github.com/LeoToso/Byz-robust-nonlinear-rep
Terminology
Sources
- LEAF: A Benchmark for Federated Settings
- Few-Shot Learning via Learning the Representation, Provably
- Personalized Federated Learning: A Meta-Learning Approach
- Adversarially Robust Multitask Adaptive Control
- Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top
- Robust Federated Learning in a Heterogeneous Environment
- Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks
- Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing
- Federated Learning: Strategies for Improving Communication Efficiency
- Partially Personalized Federated Learning: Breaking the Curse of Data Heterogeneity
- On the Gradient Heterogeneity Dynamics of Adversarially Robust Federated Regression
- FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning
- Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples
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