ICML2023_FeDXL
Official implementation of ICML 2023 paper "FeDXL: Provable Federated Learning for Deep X-Risk Optimization".
AI summary
Federated learner
An implementation of a federated learning algorithm for optimization problems with compositional pairwise risk optimization.
- stars
- 2
- forks
- 0
- watching
- 1
Similar projects
Found by comparing what the projects do, not just their names.
Federated Optimization Library
This code repository provides an implementation of Federated Composite Optimization for decentralized machine learning
Federated optimizer
An optimization framework designed to address heterogeneity in federated learning across distributed networks
Federated learning optimizer
An algorithm for distributed learning with flexible model customization during training and testing
Federated learning optimization
An approach to efficient federated learning by progressively training models on client devices with reduced communication and computation requirements.
Federated Learning Algorithm
An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data
Federated learner
Provides code for a federated learning algorithm to optimize machine learning models in a distributed setting.
federated learning optimizers
An implementation of algorithms for nonconvex federated learning optimization
Federated Learning optimizer
An algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance
Federated learner optimizer
A tool for training federated learning models with adaptive gradient balancing to handle class imbalance in multi-client scenarios.
FL optimizer
An optimization framework for federated learning
Federated Learner
An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Federated learning algorithm
An implementation of Bayesian network structure learning with continuous optimization for federated learning.
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.
Collaboration optimizer
An algorithm that optimizes collaboration in federated learning by clustering clients into non-overlapping coalitions based on data quantity and pairwise distribution distances.
