2010 LargeScaleMachineLearningwithSt

• (Bottou, 2010) ⇒ Léon Bottou. (2010). “Large-scale Machine Learning with Stochastic Gradient Descent.” In: Proceedings of COMPSTAT'2010.

Subject Headings: Large-Scale Stochastic Gradient Descent, Second-Order SGD.

Notes

• Related presentation slides: http://rocq.inria.fr/axis/COMPSTAT2010/slides/slides_17.pdf

Cited By

• http://scholar.google.com/scholar?q=%222010%22+Large-scale+Machine+Learning+with+Stochastic+Gradient+Descent

Quotes

Author Keywords

• Stochastic gradient descent; online learning

Abstract

During the last decade, the data sizes have grown faster than the speed of processors. In this context, the capabilities of statistical machine learning methods is limited by the computing time rather than the sample size. A more precise analysis uncovers qualitatively different tradeoffs for the case of small-scale and large-scale learning problems. The large-scale case involves the computational complexity of the underlying optimization algorithm in non-trivial ways. Unlikely optimization algorithms such as stochastic gradient descent show amazing performance for large-scale problems. In particular, second order stochastic gradient and averaged stochastic gradient are asymptotically efficient after a single pass on the training set.

References

;

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2010 LargeScaleMachineLearningwithSt	Léon Bottou			Large-scale Machine Learning with Stochastic Gradient Descent						2010