fedsam
by debcaldarola
AI summary
Flat minimization optimizer
Improving generalization in federated learning by seeking flat minima through optimization techniques
- stars
- 82
- forks
- 14
- watching
- 3
Similar projects
Found by comparing what the projects do, not just their names.
Decentralized optimizer
A modular JAX implementation of federated learning via posterior averaging for decentralized optimization
Federated Averaging Optimizer
An implementation of a federated averaging algorithm with an extrapolation approach to speed up distributed machine learning training on client-held data.
Federated Optimizer
An implementation of a federated optimization algorithm for distributed machine learning
Federated learner optimizer
A tool for training federated learning models with adaptive gradient balancing to handle class imbalance in multi-client scenarios.
Optimization framework
This project presents optimization techniques for federated learning and minimax games in the context of machine learning
Federated Learning Optimizer
An implementation of federated learning optimized for training on renewable energy sources and spare compute capacity to minimize carbon emissions.
federated learning optimizers
An implementation of algorithms for nonconvex federated learning optimization
Federated Learning Optimizer
Improves utility-privacy tradeoff in federated learning by reprogramming models to balance data utility and user privacy.
Federated Learning optimizer
An algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance
Federated optimizer
An optimization framework designed to address heterogeneity in federated learning across distributed networks
Federated learner
An implementation of a federated learning algorithm for optimization problems with compositional pairwise risk optimization.
Federated Learning Algorithm
This project presents an approach to federated learning with partial client participation by optimizing anchor selection for improving model accuracy and convergence.
Federated learning framework
Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions.
Federated learning optimizer
An algorithm for distributed learning with flexible model customization during training and testing
Federated learner
Federated learning algorithm that adapts to non-IID data by decoupling and correcting for local drift