1 citations · 1 across the 1 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.LG2019
SENSE: Semantically Enhanced Node Sequence Embedding
Swati Rallapalli, Liang Ma, Mudhakar Srivatsa +4
Effectively capturing graph node sequences in the form of vector embeddings is critical to many applications. We achieve this by (i) first learning vector embeddings of single grap…