As a powerful expression of human knowledge in a structural form, knowledge graph (KG)
has drawn great attention from both the academia and the industry and a large number of …

Abstract Machine learning is a powerful tool for gleaning knowledge from massive amounts
of data. While a great deal of machine learning research has focused on improving the …

This paper defines software fairness and discrimination and develops a testing-based
method for measuring if and how much software discriminates, focusing on causality in …

With the continuous and vast increase in the amount of data in our digital world, it has been
acknowledged that the number of knowledgeable data scientists can not scale to address …

Machine learning has become an essential tool for gleaning knowledge from data and
tackling a diverse set of computationally hard tasks. However, the accuracy of a machine …

There is now more data to analyze than ever before. As data volume and variety have
increased, so have the ties between machine learning and data integration become …

Errors are prevalent in time series data, which is particularly common in the industrial field.
Data with errors could not be stored in the database, which results in the loss of data assets …

In this survey, we provide an overview of the literature on knowledge graphs (KGs) in the
context of information retrieval (IR). Modern IR systems can benefit from information …

As data volumes continue to rise, manual inspection is becoming increasingly untenable. In
response, we present MacroBase, a data analytics engine that prioritizes end-user attention …

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