2015 CuckooLinearAlgebra

• (Zhou et al., 2015) ⇒ Li Zhou, David G. Andersen, Mu Li, and Alexander J. Smola. (2015). “Cuckoo Linear Algebra.” In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015). ISBN:978-1-4503-3664-2 doi:10.1145/2783258.2783263

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222015%22+Cuckoo+Linear+Algebra
• http://dl.acm.org/citation.cfm?id=2783258.2783263&preflayout=flat#citedby

Quotes

Author Keywords

• General; hashing; linear models; sparse vectors

Abstract

In this paper we present a novel data structure for sparse vectors based on Cuckoo hashing. It is highly memory efficient and allows for random access at near dense vector level rates. This allows us to solve sparse l₁ programming problems exactly and without preprocessing at a cost that is identical to dense linear algebra both in terms of memory and speed. Our approach provides a feasible alternative to the hash kernel and it excels whenever exact solutions are required, such as for feature selection.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2015 CuckooLinearAlgebra	Alexander J. Smola Mu Li Li Zhou David G. Andersen			Cuckoo Linear Algebra				10.1145/2783258.2783263		2015