We present a novel, purely affinity-based natural image matting algorithm. Our method relies
on carefully defined pixel-to-pixel connections that enable effective use of information …

Developers often prefer flexibility over upfront schema design, making semi-structured data
formats such as JSON increasingly popular. Large amounts of JSON data are therefore …

Industry and academia are continuously becoming more data-driven and data-intensive,
relying on the analysis of a wide variety of heterogeneous datasets to gain insights. The …

Scientific discoveries are increasingly driven by analyzing large volumes of image data.
Many new libraries and specialized database management systems (DBMSs) have …

Error-bounded lossy compression is one of the most effective techniques for reducing
scientific data sizes. However, the traditional trial-and-error approach used to configure …

As the size of data and its heterogeneity increase, traditional database system architecture
becomes an obstacle to data analysis. Integrating and ingesting (loading) data into …

There has been a recent flurry of interest in providing query capability on raw data in today's
big data systems. These raw data must be parsed before processing or use in analytics …

The constant flux of data and queries alike has been pushing the boundaries of data
analysis systems. The increasing size of raw data files has made data loading an expensive …

The constant flux of data and queries alike has been pushing the boundaries of data
analysis systems. The increasing size of raw data files has made data loading an expensive …

Scientific data sets, which grow rapidly in volume, are often attached with plentiful metadata,
such as their associated experiment or simulation information. Thus, it becomes difficult for …