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ICML
2009
IEEE

Feature hashing for large scale multitask learning

10 years 2 months ago
Feature hashing for large scale multitask learning
Empirical evidence suggests that hashing is an effective strategy for dimensionality reduction and practical nonparametric estimation. In this paper we provide exponential tail bounds for feature hashing and show that the interaction between random subspaces is negligible with high probability. We demonstrate the feasibility of this approach with experimental results for a new use case — multitask learning with hundreds of thousands of tasks.
Kilian Q. Weinberger, Anirban Dasgupta, John Langf
Added 19 May 2010
Updated 19 May 2010
Type Conference
Year 2009
Where ICML
Authors Kilian Q. Weinberger, Anirban Dasgupta, John Langford, Alexander J. Smola, Josh Attenberg
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