Out-of-Distribution Federated Distillation with Domain-Aware Proxy
Jiahao Xiao, Jiangming Liu
cs.LG
Submitted: 2026-08-09
Updated: 2026-08-11
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Large scale distributed neural network training through online distillation
- Anomaly Detection under Distribution Shift
- Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation
- In Search of Lost Domain Generalization
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
- Distilling the Knowledge in a Neural Network
- FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
- Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data
- FedMD: Heterogenous Federated Learning via Model Distillation
- Is Synthetic Data From Diffusion Models Ready for Knowledge Distillation?
- Ensemble Distillation for Robust Model Fusion in Federated Learning
- On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey
- Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization
- Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions
- Exploiting Personalized Invariance for Better Out-of-distribution Generalization in Federated Learning
- Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory
- Diffusion Model-Based Data Synthesis Aided Federated Semi-Supervised Learning
- Adaptive Federated Distillation for Multi-Domain Non-IID Textual Data
- FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models
- What Do We Mean by Generalization in Federated Learning?
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