A fault‐tolerant and scalable boosting method over vertically partitioned data

Today's article comes from CAAI Transactions on Intelligence Technology. The authors are Jiang et al., from Arkansas State University. In this paper they present FedBoost, a method for overcoming two common issues with Federated Learning: the straggler problem and scalability. Let's dive in.

DOI: 10.1049/cit2.12339

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