Abstract Machine Learning (ML) is integrated into a growing number of systems for various
applications. Because the performance of an ML model is highly dependent on the quality of …

Healthcare organizations have realized that Artificial intelligence (AI) can provide a
competitive edge through personalized patient experiences, improved patient outcomes …

Drinking water is essential to public health and socioeconomic growth. Therefore, assessing
and ensuring drinking water supply is a critical task in modern society. Conventional …

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 …

Traditional cost-based optimizers are efficient and stable to generate optimal plans for
simple SQL queries, but they may not generate high-quality plans for complicated queries …

Extracting data insights and generating visual data stories from tabular data are critical parts
of data analysis. However, most existing studies primarily focus on tabular data stored as flat …

The lack of sufficient labeled data is a key bottleneck for practitioners in many real-world
supervised machine learning (ML) tasks. In this paper, we study a new problem, namely …

Sufficient good features are indispensable to train well-performed machine learning models.
However, it is com-mon that good features are not always enough, where feature …

Finding line-chart images similar to a given line-chart image query is a common task in data
exploration and image query systems, eg finding similar trends in stock markets or medical …

Given a dataset with incomplete data (eg, missing values), training a machine learning
model over the incomplete data requires two steps. First, it requires a data-effective step that …