Big data analytics is the key research subject for future data driven decision making
applications. Due to the large amount of data, progressive analytics could provide an …

Analytics over the increasing quantity of data stored in the Cloud has become very
expensive, particularly due to the pay-as-you-go Cloud computation model. Data scientists …

Current applications require the processing of huge amounts of data produced by
applications or end users personal devices. In such settings, intelligent analytics on top of …

With the continuous development of the Internet and information technology, more and more
mobile terminals, wear equipment etc. contribute to the tremendous data. Thanks to the …

Incremental gradient descent is a general technique to solve a large class of convex
optimization problems arising in many machine learning tasks. GLADE is a parallel …

As data-intensive cluster computing systems like MapReduce grow in popularity, there is a
strong need to promote the efficiency. Recurring queries, repeatedly being executed for long …

Data science requires time-consuming iterative manual activities. In particular, activities
such as data selection, preprocessing, transformation, and mining, highly depend on …

Collecting, analyzing and gaining insight from large volumes of data is now the norm in an
ever increasing number of industries. Data analytics techniques, such as machine learning …

The enormous growth of the internet, enterprise applications, social media, and IoT devices
in the current time caused a huge spike in enterprise data growth. Big data platform provided …

In recent years “big data” has become something of a buzzword in business, computer
science, information studies, information systems, statistics, and many other fields. As …