Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/67356
Type: Journal article
Title: Hash Kernels for Structured Data
Author: Shi, Q.
Petterson, J.
Dror, G.
Langford, J.
Smola, A.
Vishwanathan, S.
Citation: Journal of Machine Learning Research (Print), 2009; 10:2615-2637
Publisher: MIT Press
Issue Date: 2009
ISSN: 1532-4435
1533-7928
Statement of
Responsibility: 
Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alex Smola and S.V.N. Vishwanathan
Abstract: We propose hashing to facilitate efficient kernels. This generalizes previous work using sampling and we show a principled way to compute the kernel matrix for data streams and sparse feature spaces. Moreover, we give deviation bounds from the exact kernel matrix. This has applications to estimation on strings and graphs
Keywords: hashing, stream, string kernel, graphlet kernel, multiclass classification
Rights: © 2009 Authors. Copyright © JMLR 2009. All rights reserved.
RMID: 0020112762
Published version: http://jmlr.csail.mit.edu/papers/v10/
Appears in Collections:Computer Science publications

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