The Internet of Things (IoT) envisions a world-wide, interconnected network of smart
physical entities. These physical entities generate a large amount of data in operation, and …

Large-scale data analytics using statistical machine learning (ML), popularly called
advanced analytics, underpins many modern data-driven applications. The data …

Recent efforts applying machine learning techniques to query optimization have shown few
practical gains due to substantive training overhead, inability to adapt to changes, and poor …

Configuration tuning is vital to optimize the performance of database management system
(DBMS). It becomes more tedious and urgent for cloud databases (CDB) due to the diverse …

We live in an increasingly interconnected world, with many organizations operating across
countries or even continents. To serve their global user base, organizations are replacing …

Hybrid Transactional and Analytical Processing (HTAP) databases require processing
transactional and analytical queries in isolation to remove the interference between them. To …

High dimensional black-box optimization has broad applications but remains a challenging
problem to solve. Given a set of samples xi, yi, building a global model (like Bayesian …

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 …

Although learning-based database optimization techniques have been studied from
academia in recent years, they have not been widely deployed in commercial database …

In recent years, there has been an explosion of large-scale real-time analytics needs and a
plethora of streaming systems have been developed to support such applications. These …