Hash Kernels for Structured Data

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dc.contributor.authorShi, Qinfeng
dc.contributor.authorPetterson, James
dc.contributor.authorDror, Gideon
dc.contributor.authorLangford, John
dc.contributor.authorSmola, Alexander
dc.contributor.authorVishwanathan, S.V.N.
dc.date.accessioned2015-12-10T22:39:44Z
dc.date.issued2009
dc.date.updated2016-02-24T11:44:41Z
dc.description.abstractWe 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
dc.identifier.issn1532-4435
dc.identifier.urihttp://hdl.handle.net/1885/57316
dc.publisherMIT Press
dc.sourceJournal of Machine Learning Research
dc.source.urihttp://jmlr.csail.mit.edu/papers/v10
dc.subjectKeywords: Data stream; Feature space; Kernel matrices; Multi-class classification; String Kernel; Structured data; Hydraulics Graphlet kernel; Hashing; Multiclass classification; Stream; String kernel
dc.titleHash Kernels for Structured Data
dc.typeJournal article
local.bibliographicCitation.lastpage2637
local.bibliographicCitation.startpage2615
local.contributor.affiliationShi, Qinfeng, College of Engineering and Computer Science, ANU
local.contributor.affiliationPetterson, James, College of Engineering and Computer Science, ANU
local.contributor.affiliationDror, Gideon, Academic College of Tel-Aviv-Yaffo
local.contributor.affiliationLangford, John, Yahoo Research
local.contributor.affiliationSmola, Alexander, Yahoo! Research
local.contributor.affiliationVishwanathan, S.V.N., Purdue University
local.contributor.authoremailrepository.admin@anu.edu.au
local.contributor.authoruidShi, Qinfeng, u4265690
local.contributor.authoruidPetterson, James, u4607026
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.ariespublicationu8803936xPUB395
local.identifier.citationvolume10
local.identifier.scopusID2-s2.0-73549107233
local.identifier.uidSubmittedByu8803936
local.type.statusPublished Version

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