Cardinality estimation (CardEst) plays a significant role in generating high-quality query
plans for a query optimizer in DBMS. In the last decade, an increasing number of advanced …

Rule discovery from large datasets is often prohibitively costly. The problem becomes more
staggering when the rules are collectively defined across multiple tables. To scale with large …

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 …

This paper overviews an approach that addresses machine learning over relational data as
a database problem. This is justified by two observations. First, the input to the learning task …

Subgraph counting is a fundamental component for many downstream applications such as
graph representation learning and query optimization. Since obtaining the exact count is …

Despite decades of research on approximate query processing (AQP), our understanding of
sample-based joins has remained limited and, to some extent, even superficial. The …

SPARQL property path queries provide a succinct way to write complex navigational queries
over RDF knowledge graphs. However, their evaluation remains difficult as they may involve …

This tutorial overviews the state of the art in learning models over relational databases and
makes the case for a first-principles approach that exploits recent developments in database …

Accurately estimating the cardinality (ie, the number of answers) of complex queries plays a
central role in database systems. This problem is particularly difficult in graph databases …

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 …