Scalable and Numerically Stable Descriptive Statistics in SystemML

@article{Tian2012ScalableAN,
  title={Scalable and Numerically Stable Descriptive Statistics in SystemML},
  author={Yuanyuan Tian and Shirish Tatikonda and Berthold Reinwald},
  journal={2012 IEEE 28th International Conference on Data Engineering},
  year={2012},
  pages={1351-1359}
}
With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. SystemML is a framework that employs a declarative approach for large scale data analytics. In SystemML, machine learning algorithms are expressed as scripts in a high-level language, called DML, which is syntactically similar to R. DML scripts are compiled, optimized, and executed in the SystemML runtime that is built… CONTINUE READING