near-optimal-federated
by clreda
AI summary
Collaborative Bandit Solver
An open-source software project implementing collaborative learning in bandits to achieve near-optimal results
- stars
- 1
- forks
- 1
- watching
- 1
Similar projects
Found by comparing what the projects do, not just their names.
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.
Federated learner
An implementation of a federated learning algorithm for optimization problems with compositional pairwise risk optimization.
Federated bandit algo
Implementation of algorithms for federated linear bandits in multi-agent environments
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 Optimizer
An implementation of a federated optimization algorithm for distributed machine learning
Federated learning algorithm
An implementation of Bayesian network structure learning with continuous optimization for federated learning.
Federated Learning Algorithm
An implementation of federated learning algorithm to reduce local learning bias and improve convergence on heterogeneous data
Decentralized optimizer
A modular JAX implementation of federated learning via posterior averaging for decentralized optimization
Federated optimizer
An optimization framework designed to address heterogeneity in federated learning across distributed networks
Federated Learning optimizer
An algorithm for Federated Learning with heterogeneous data, designed to optimize deep neural networks and improve performance
Collab ML framework
An open source framework for collaborative machine learning with data distributed across multiple institutions.
Federated learner
This project presents a federated semi-supervised learning approach to improve model performance on multiple datasets by leveraging random sampling consensus.
Federated Learning
Enabling multiple agents to learn from heterogeneous environments without sharing their knowledge or data
Federated learning optimization
An approach to efficient federated learning by progressively training models on client devices with reduced communication and computation requirements.
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.
