Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …

Recent work on" learned indexes" has changed the way we look at the decades-old field of
DBMS indexing. The key idea is that indexes can be thought of as" models" that predict the …

Filtering data based on predicates is one of the most fundamental operations for any modern
data warehouse. Techniques to accelerate the execution of filter expressions include …

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …

Machine learning, especially deep learning, is used increasingly to enable better solutions
for data management tasks previously solved by other means, including database indexing …

Index plays an essential role in modern database engines to accelerate the query
processing. The new paradigm of" learned index" has significantly changed the way of …

Query optimizers rely on accurate cardinality estimation (CardEst) to produce good
execution plans. The core problem of CardEst is how to model the rich joint distribution of …

Corporations today collect data at an unprecedented and accelerating scale, making the
need to run queries on large datasets increasingly important. Technologies such as …

RDMA (Remote Direct Memory Access) has gained considerable interests in network-
attached in-memory key-value stores. However, traversing the remote tree-based index in …

Indexes can improve query-processing performance by avoiding full table scans. Although
traditional indexes (eg, B+-tree) have been widely used, learned indexes are proposed to …