FedTHE
by LINs-lab
[ICLR 2023] Test-time Robust Personalization for Federated Learning
AI summary
Personalization software
Improves machine learning models for personalized performance under evolving test distributions in distributed environments
- stars
- 53
- forks
- 3
- watching
- 2
Similar projects
Found by comparing what the projects do, not just their names.
Federated Learning Algorithm
An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data
Federated Learning Framework
Personalized Subgraph Federated Learning framework for distributed machine learning
Personalized Learning Model Trainer
This project enables personalized learning models by collaborating on learning the best strategy for each client
Federated Learning Framework
A framework for federated learning with partial model personalization
Feature separator
A framework that separates feature information from data in federated learning to enable personalized models.
Federated learning framework
Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.
Federated Learning
This project enables personalized federated learning with inferred collaboration graphs to improve the performance of machine learning models on non-IID (non-independent and identically distributed) datasets.
Federated Learning optimizer
An algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance
Federated learner
An implementation of a federated learning algorithm for optimization problems with compositional pairwise risk optimization.
Federated Learning Simulator
Simulates a federated learning setting to preserve individual data privacy
Federated Learning Framework
A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems.
Federated Learning Framework
Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models.
Federated Learning Optimizer
Improves utility-privacy tradeoff in federated learning by reprogramming models to balance data utility and user privacy.
Personalized Fed Learning Model
An implementation of personalized federated learning using variational Bayesian inference on the MNIST dataset
Federated learning optimizer
An algorithm for distributed learning with flexible model customization during training and testing