DELTA_FL
by L3030
[NeurIPS 2023]DELTA: Diverse Client Sampling for Fasting Federated Learning
AI summary
FL sampler
An implementation of an unbiased Federated Learning sampling scheme designed to improve model convergence and reduce variance in client participation.
- stars
- 5
- forks
- 0
- watching
- 2
Similar projects
Found by comparing what the projects do, not just their names.
Federated learner
An implementation of a federated learning algorithm for handling heterogeneous data
FL analysis
Analyzes Federated Learning with Arbitrary Client Participation using various optimization strategies and datasets.
ML data reader
A Python library that provides a Delta Lake table reader for the Ray open-source ML toolkit
Federated learner
An adaptive federated learning framework for heterogeneous clients with resource constraints.
Federated Learning Library
An implementation of federated learning with sparse training and readjustment mechanisms to reduce communication overhead while maintaining model performance.
Federated learning library
An implementation of federated learning with prototype-based methods across heterogeneous clients
FL algorithm
An algorithm for Federated Learning that handles client subsampling and data heterogeneity with unbounded smoothness
Model sampler
Provides an API for sampling quadratic and higher-order models used in optimization algorithms
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.
FL defense tool
A toolkit for federated learning with a focus on defending against data heterogeneity
Federated learner
Provides code for a federated learning algorithm to optimize machine learning models in a distributed setting.
Client selection method
Proposes a method for selecting a diverse subset of clients in federated learning to improve convergence and fairness
Federated Learning Algorithms
Implementation of various federated learning algorithms to mitigate dimensional collapse in heterogeneous federated learning environments
Federated Learning Simulator
Simulates a federated learning setting to preserve individual data privacy
Federated Learning Algorithm
An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data