Sentence examples for with large scale data from inspiring English sources

Examples include using a distributed network of video game players to assist in solving protein folding problems (Markoff 2010), and leveraging Amazon's Mechanical Turk crowdsourcing marketplace platform to assist with large scale data processing and coding functions that cannot be automated (Conley & Tosti-Kharas 2010; Chen et al. 2011).

A Gaussian kernel was chosen in order to simplify calculations with large scale data.

The relatively very low variance associated with GM concurs with large scale data of GM maize and soybean [35].

Often the responsibility for dealing with large scale data management falls to biostatisticians in addition to more traditional research efforts, though the growth of medical informatics is creating a need for informatics specialists who may or may not utilize statistical analysis in their work, focusing instead on Data Science and empirical models [ 10].

"Clear water" is a scale-dependent concept, so it is more likely to successfully find the "clear water" from images with smaller scale than that with larger scale data.

SVM learning is also time consuming in dealing with large-scale data.

Sakoda also gave us his thoughts on where the next wave of innovation will take place with large-scale data processing.

In order to deal with large-scale data efficiently, a parallel and distributed cluster with good scalability, flexibility, and fault tolerance is needed.

In future, we will keep on improving the MIML learning techniques on the ability of dealing with large-scale data, efficiency, parallel implementations, etc., and promote the effectiveness for expanding the applicability of MIML in other applications.

In addition to distributed theoretical framework for machine learning to mitigate the challenges related to high volumes, some practicable parallel programming methods are also proposed and applied to learning algorithms to deal with large-scale data sets.

Future work includes extending the framework to deal with large-scale data sets, to incorporate novel data analytics techniques specifically defined for tasks such as user sentiment analysis and to incorporate novel IoT technologies.