bias_in_FL
This is the code repository for the paper titled "Bias Propagation in Federated Learning" which was accepted to the International Conference on Learning Representations (ICLR) 2023.
AI summary
Bias detection tool
This project investigates how bias can be introduced and spread in machine learning models during federated learning, and aims to detect and mitigate this issue.
- stars
- 11
- forks
- 2
- watching
- 2
Similar projects
Found by comparing what the projects do, not just their names.
Bias detector
A dataset and benchmarking framework to evaluate the performance of question answering models on detecting and mitigating social biases.
Privacy Auditor
An auditing tool to assess the privacy risks of machine learning models
Bias auditor
Toolkit to audit and mitigate biases in machine learning models
Bias datasets
Compiles bias evaluation datasets and provides access to original data sources for large language models
Bias auditor
A software package for auditing and analyzing machine learning models to detect unfair biases
FL analysis
Analyzes Federated Learning with Arbitrary Client Participation using various optimization strategies and datasets.
Federated Learning Attack
This project presents an attack on federated learning systems to compromise their privacy-preserving mechanisms.
ethicalml/xai1.1K
Bias analysis tool
An eXplainability toolbox for machine learning that enables data analysis and model evaluation to mitigate biases and improve performance
Domain adaptation library
An implementation of a federated learning method to reduce domain bias in representation space, enabling improved knowledge transfer between clients and servers.
Fair learning algorithm
This project develops and evaluates algorithms for fair resource allocation in federated learning, aiming to promote more inclusive AI systems.
Fairness mechanism library
Provides a Python implementation of fairness mechanisms in classification models to mitigate disparate impact and mistreatment.
Bias detector
A tool for detecting bias in machine learning models and mitigating it using various techniques.
Bias correction software
A collection of bias correction techniques for climate data analysis
Federated Breach Analysis
A PyTorch framework for analyzing vulnerabilities in federated learning models and predicting data breaches
FL defense tool
A toolkit for federated learning with a focus on defending against data heterogeneity
