37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
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Updated
Nov 3, 2024 - Python
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
Personalized federated learning codebase for research
AAAI 2023 accepted paper, FedALA: Adaptive Local Aggregation for Personalized Federated Learning
PyTorch implementation of Federated Learning algorithms FedSGD, FedAvg, FedAvgM, FedIR, FedVC, FedProx and standard SGD, applied to visual classification. Client distributions are synthesized with arbitrary non-identicalness and imbalance (Dirichlet priors). Client systems can be arbitrarily heterogeneous. Several mobile-friendly models are prov…
Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system.
A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures
Implementation of Federated Learning using the Flower Framework
Official implementation of paper "Brain Age Estimation Using Structural MRI: A Clustered Federated Learning Approach"
Federated Learning for Sentiment Analysis
This is a Tensorflow implementation of the paper Homogeneous Learning: Self-Attention Decentralized Deep Learning.
Membership Inference Attacks on Imbalanced Federated Learning setups
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