112 citations · 113 across the 2 of their papers we have counts for
2 papers
cs.CL2020★ 1 cited
SEEC: Semantic Vector Federation across Edge Computing Environments
Shalisha Witherspoon, Dean Steuer, Graham Bent +1
Semantic vector embedding techniques have proven useful in learning semantic representations of data across multiple domains. A key application enabled by such techniques is the ab…
cs.LG2020★ 112 cited
IBM Federated Learning: an Enterprise Framework White Paper V0.1
Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas +21
Federated Learning (FL) is an approach to conduct machine learning without centralizing training data in a single place, for reasons of privacy, confidentiality or data volume. How…