Deep Learning (DL) has achieved great success in many real applications. Despite its
success, there are some main problems when deploying advanced DL models in database …

A knowledge graph (KG) manages large-scale and real-world facts as a big graph in a
schema-flexible manner. Aggregate query is a fundamental query over KGs, eg,“what is the …

As data analytics becomes more crucial to digital systems, so grows the importance of
characterizing the database queries that admit a more efficient evaluation. We consider the …

Interactive time responses are a crucial requirement for users analyzing large amounts of
data, typically stored in a relational style data-warehouse where data is partitioned across …

Joining records with all other records that meet a linkage condition can result in an
astronomically large number of combinations due to many-to-many relationships. For such …

Exploration systems over large-scale RDF knowl-edge graphs often rely on aggregate count
queries to indicate how many results the user can expect for the possible next steps of …

Large scale data analytics over geographically distributed data sources is challenging
primarily due to the constrained and heterogeneous resource availability such as the wide …

The appealing properties of secure hardware solutions such as trusted execution
environment (TEE) including low computational overhead, confidentiality guarantee, and …

With the advent of data-driven operating model, deriving useful insights from big data
analysis has become very important. But the ever-increasing volume of data has made …

In the current world, OLAP (Online Analytical Processing) is used intensively by modern
organizations to perform ad hoc analysis of data, providing insight for better decision …