23 citations · 25 across the 5 of their papers we have counts for
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cs.LG2024
FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning
Jordan Slessor, Dezheng Kong, Xiaofen Tang +2
Federated learning (FL) is a machine learning methodology that involves the collaborative training of a global model across multiple decentralized clients in a privacy-preserving w…
stat.ML2024★ 2 cited
Statistical Undersampling with Mutual Information and Support Points
Alex Mak, Shubham Sahoo, Shivani Pandey +2
Class imbalance and distributional differences in large datasets present significant challenges for classification tasks machine learning, often leading to biased models and poor p…