Information Technology Reference
In-Depth Information
12. Chiba, S., and M. Nishizawa. An easy-to-use toolkit for efficient Java Bytecode
translators. In International Conference on Generative Programming and Component
Engineering . 2003.
13. Syed, b.N.A., et al. Incremental learning with support vector machines. In
International Knowledge Discovery and Data Mining Conference . 1999.
14. Graf, H. P., et al., Parallel support vector machines: the cascade SVM . Advances
in Neural Information Processing Systems , 2004, 17: 521-528.
15. Guha, S., Computing Environment for the Statistical Analysis of Large and
Complex Data, doctoral dissertation, Purdue University, 2010.
16. Rickert, J., Big Data Analysis with Revolution R Enterprise. White paper. Mountain
View, CA: Revolution Analytics, 2011.
17. bigmemory. http://cran.r-project.org/web/packages/bigmemory/index.html.
18. Das, S., et al. Ricardo: integrating R and Hadoop. In ACM International conference
on Management of Data. 2010.
19. RJDBC. http://www.rforge.net/RJDBC/index.html.
20. RMySQL. http://cran.r-project.org/web/packages/RMySQL/.
21. RHive. Available from: https://github.com/nexr/RHive.
22. Open MPI. http://www.open-mpi.org/.
23. Rmpi. http://www.stats.uwo.ca/faculty/yu/Rmpi/.
24. snow. http://cran.r-project.org/web/packages/snow/index.html.
25. cloudRmpi. http://norbl.com/cloudrmpi/cloudRmpi.html.
26. Chine, K., Open science in the cloud: towards a universal platform for scien-
tific and statistical computing. In Handbook of Cloud Computing , B. Furht and
A. Escalante, editors. New York: Springer, 2010, pp. 453-474.
27. Ghoting, A., et al. SystemML: declarative machine learning on MapReduce.
In  IEEE International Conference on Data Engineering . 2011.
28. Kraska, T., et al., MLbase: A Distributed Machine Learning System. In The
Conference on Innovative Data Systems Research . 2013.
29. Cloudera ML. https://github.com/cloudera/ml.
Search WWH ::




Custom Search