Visualizations themselves have become a data format. Akin to other data formats such as
text and images, visualizations are increasingly created, stored, shared, and (re-) used with …

Supporting the translation from natural language (NL) query to visualization (NL2VIS) can
simplify the creation of data visualizations because if successful, anyone can generate …

Inspired by the great success of machine learning (ML), researchers have applied ML
techniques to visualizations to achieve a better design, development, and evaluation of …

Natural language (NL) is a promising interaction paradigm for data visualization (VIS).
However, there are not any NL to VIS (NL2VIS) benchmarks available. Our goal is to provide …

Machine learning (ML) has widespread applications and has revolutionized many
industries, but suffers from several challenges. First, sufficient high-quality training data is …

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 …

Generative AI has made significant strides, yet concerns about the accuracy and reliability of
its outputs continue to grow. Such inaccuracies can have serious consequences such as …

Outlier detection is critical to a large number of applications from finance fraud detection to
health care. Although numerous approaches have been proposed to automatically detect …

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 …

This paper introduces the open-source Beast system for scalable exploratory data science
on big spatio-temporal data. Beast is based on well-established research and has been …