Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

A wide spectrum of design and decision problems, including parameter tuning, A/B testing
and drug design, intrinsically are instances of black-box optimization. Bayesian optimization …

Knob tuning plays an important role in database optimization, which tunes knob settings to
optimize the database performance or improve resource utilization. However, there are …

Modern database management systems (DBMS) expose hundreds of configurable knobs to
control system behaviours. Determining the appropriate values for these knobs to improve …

Black-box optimization (BBO) has a broad range of applications, including automatic
machine learning, engineering, physics, and experimental design. However, it remains a …

Tuning a database system to achieve optimal performance on a given workload is a long-
standing problem in the database community. A number of recent works have leveraged ML …

The performance optimization of database systems has been widely studied for years. From
the perspective of the operation and maintenance personnel, it mainly includes three topics …

Learned databases, or AI4DB techniques, have rapidly developed in the last decade.
Deploying machine learning (ML) and AI4DB algorithms into actual databases is the gold …

Two decades ago, one of us co-authored a paper commenting on the previous 40 years of
data modelling research and development [188]. That paper demonstrated that the relational …

We consider the problem of optimizing expensive black-box functions over high-dimensional
combinatorial spaces which arises in many science, engineering, and ML applications. We …