Recent data search platforms use ML task-based utility measures rather t...
High-quality machine learning models are dependent on access to high-qua...
AutoML services provide a way for non-expert users to benefit from
high-...
Pooling and sharing data increases and distributes its value. But since ...
Data is a central component of machine learning and causal inference tas...
Data discovery systems help users identify relevant data among large tab...
Identifying a project-join view (PJ-view) over collections of tables is ...
Scalable data science requires access to metadata, which is increasingly...
This paper introduces Data Stations, a new data architecture that we are...
Automatic machine learning () is a family of techniques to automate the
...
Data only generates value for a few organizations with expertise and
res...
Many data problems are solved when the right view of a combination of
da...
Much like on-premises systems, the natural choice for running database
a...
Data-driven analysis is important in virtually every modern organization...
As neural networks become widely deployed in different applications and ...
Many database columns contain string or numerical data that conforms to ...