\begin{thebibliography}{19}
\expandafter\ifx\csname natexlab\endcsname\relax\def\natexlab#1{#1}\fi
\expandafter\ifx\csname url\endcsname\relax
  \def\url#1{{\tt #1}}\fi

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B.~E. Boser, I.~M. Guyon, and V.~N. Vapnik.
\newblock A training algorithm for optimal margin classifiers.
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\bibitem[Cavnar(1994)]{cavnar95}
W.~B. Cavnar.
\newblock Using an n-gram based document representation with a vector
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\newblock In D.~K. Harman, editor, {\em Proceedings of {TREC} --3, 3rd Text
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N.~Cristianini, A.~Elisseef, and J.~Shawe-Taylor.
\newblock On optimizing kernel alignment.
\newblock Technical Report NC-TR-01-087, Royal Holloway, University of London,
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\bibitem[Cristianini et~al.(to appear)Cristianini, Elisseef, and
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N.~Cristianini, A.~Elisseef, and J.~Shawe-Taylor.
\newblock On kernel-target alignment.
\newblock In {\em Neural Information Processing System (NIPS '01)}, to appear.

\bibitem[Cristianini and Shawe-Taylor(2000)]{CriSha-book}
N.~Cristianini and J.~Shawe-Taylor.
\newblock {\em An introduction to Support Vector Machines}.
\newblock Cambridge University Press, Cambridge, UK, 2000.

\bibitem[Friess et~al.(1998)Friess, Cristianini, and Campbell]{KA-ICML}
T.~Friess, N.~Cristianini, and C.~Campbell.
\newblock The kernel-adatron: a fast and simple training procedure for support
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\newblock In J.~Shavlik, editor, {\em Proceedings of the 15th International
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\bibitem[Haussler(1999)]{Haussler99}
D.~Haussler.
\newblock Convolution kernels on discrete structures.
\newblock Technical Report UCSC-CRL-99-10, University of California in Santa
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\bibitem[Huffman(1995)]{huffman96}
S.~Huffman.
\newblock Acquaintance: Language-independent document categorization by
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\newblock In D.~K. Harman and E.~M. Voorhees, editors, {\em Proceedings of
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\newblock http://trec.nist.gov/pubs/trec4/t3proceedings.html.

\bibitem[Joachims(1998)]{Joa}
T.~Joachims.
\newblock Text categorization with support vector machines: Learning with many
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\newblock In Claire N{\'e}dellec and C{\'e}line Rouveirol, editors, {\em
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\bibitem[Joachims(1999)]{joachims}
T.~Joachims.
\newblock Making large--scale {SVM} learning practical.
\newblock In B.~Sch{\"o}lkopf, C.~J.~C. Burges, and A.~J. Smola, editors, {\em
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\bibitem[Lodhi et~al.(2001)Lodhi, Shawe-Taylor, Cristianini, and
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H.~Lodhi, J.~Shawe-Taylor, N.~Cristianini, and C.~Watkins.
\newblock Text classification using string kernels.
\newblock In T.~K. Leen, T.~G. Dietterich, and V.~Tresp, editors, {\em
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\bibitem[Mercer(1909)]{Mercer}
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\newblock Functions of positive and negative type and their connection with the
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\newblock {\em Philosophical Transactions of the Royal Society London (A)},
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\bibitem[Salton et~al.(1975)Salton, Wong, and Yang]{Saltonetal75}
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\newblock A vector space model for automatic indexing.
\newblock {\em Communications of the ACM}, 18\penalty0 (11):\penalty0 613--620,
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\bibitem[{Sch\"olkopf}(1997)]{Scholkopf97}
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\newblock {\em Support Vector Learning}.
\newblock R.~Oldenbourg Verlag, {M\"unchen}, 1997.
\newblock Doktorarbeit, Technische Universit{\"a}t Berlin. Available from
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\bibitem[{Sch\"olkopf} et~al.(1999){Sch\"olkopf}, Mika, Burges, Knirsch,
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\newblock Input space vs. feature space in kernel-based methods.
\newblock {\em IEEE Transactions on Neural Networks}, 10\penalty0 (5):\penalty0
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\bibitem[Smola and Sch\"olkopf(2000)]{SmoSch}
A.~J. Smola and B.~Sch\"olkopf.
\newblock Sparse greedy matrix approximation for machine learning.
\newblock In P.~Langley, editor, {\em Proceedings of the Seventeenth
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\bibitem[Vapnik(1995)]{Vapnik95}
V.~Vapnik.
\newblock {\em The Nature of Statistical Learning Theory}.
\newblock Springer Verlag, New York, 1995.

\bibitem[Watkins(2000)]{Watkins00}
C.~Watkins.
\newblock Dynamic alignment kernels.
\newblock In A.~J. Smola, P.~L. Bartlett, B.~Sch{\"o}lkopf, and D.~Schuurmans,
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  MA, 2000. {MIT} Press.

\bibitem[Williams and Seeger(2001)]{willsee}
C.~Williams and M.~Seeger.
\newblock Using the {N}ystr{\"o}m method to speed up kernel machines.
\newblock In T.~K. Leen, T.~G. Dietterich, and V.~Tresp, editors, {\em
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\end{thebibliography}