fedpvr
by lyn1874
Implementation for paper "Partial Variance Reduction improves Non-Convex Federated learning on heterogeneous data"
AI summary
Federated learner
An implementation of a federated learning algorithm for handling heterogeneous data
- stars
- 6
- forks
- 1
- watching
- 1
Similar projects
Found by comparing what the projects do, not just their names.
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Federated learner
Provides code for a federated learning algorithm to optimize machine learning models in a distributed setting.
Federated Learning framework
An implementation of heterogeneous federated learning with parallel edge and server computation
Federated Learning Algorithm
An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data
Federated Learning Study
The purpose of this project is to investigate the convergence of a federated learning algorithm on non-IID (non-identically and independently distributed) data.
Federated Learner
An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships
Federated learning library
An implementation of federated learning with prototype-based methods across heterogeneous clients
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 optimizer
An optimization framework designed to address heterogeneity in federated learning across distributed networks
Federated Learning framework
An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources.
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 Framework
Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models.
Federated Learning Method
An implementation of a domain generalization method for federated learning using Python and PyTorch
Heterogeneity fixer
Combating heterogeneity in federated learning by combining adversarial training with client-wise slack during aggregation