Testing and Benchmarking Large-Scale Machine Learning Systems

Thomas Breuel
Proceedings of the Snowbird Learning Workshop 2007, Puerto Rico, USA, Snowbird, 2007

Abstract:

Our research lab is currently developing a number of large-scale pattern recognitions systems incorporating novel machine learning algorithms, including an adaptive OCR engine for the Google Book Search project and a real-time network monitoring analysis system for a a large telecom provider. We have found existing toolboxes (e.g., R, SPIDER) to be inadequate to support the data management benchmarking, model selection, and validation necessary for the development of such large scale systems. In addition, we find that benchmarking results reported in the literature frequently lack sound control experiments and important text cases.

Files:

  TmbTestingAndBenchmarkingMLSys.pdf

BibTex:

@inproceedings{ BREU2007,
	Title = {Testing and Benchmarking Large-Scale Machine Learning Systems},
	Author = {Thomas Breuel},
	BookTitle = {Proceedings of the Snowbird Learning Workshop 2007},
	Year = {2007},
	Publisher = {Snowbird}
}

     
Last modified:: 30.08.2016