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Found 3 papers, 2 papers with code
On the Vulnerability of Backdoor Defenses for Federated Learning
Federated Learning (FL) is a popular distributed machine learning paradigm that enables jointly training a global model without sharing clients' data.
Loss Tolerant Federated Learning
Federated learning has attracted attention in recent years for collaboratively training data on distributed devices with privacy-preservation.
FLFE: A Communication-Efficient and Privacy-Preserving Federated Feature Engineering Framework
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques and is a key step to improve the performance of machine learning algorithms.
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