State-of-the-art congestion control algorithms for data centers alone do...
Performance variability management is an active research area in
high-pe...
Federated learning makes it possible for all parties with data isolation...
Federated learning trains models across devices with distributed data, w...
Recurrence data arise from multi-disciplinary domains spanning reliabili...
Knowledge representation learning has received a lot of attention in the...
This paper presents a new technique for migrating data between different...
Public policy making has direct and indirect impacts on social behaviors...
In Big Data environment, one pressing challenge facing engineers is to
p...
Knowledge graph embedding aims at modeling entities and relations with
l...
Knowledge representation learning aims at modeling knowledge graph by
en...
Recent neural models for data-to-text generation are mostly based on
dat...
Recent neural models for data-to-document generation have achieved remar...
OCR character segmentation for multilingual printed documents is difficu...
To date, there have been massive Semi-Structured Documents (SSDs) during...