\begin{thebibliography}{12}
\expandafter\ifx\csname natexlab\endcsname\relax\def\natexlab#1{#1}\fi
\expandafter\ifx\csname url\endcsname\relax
  \def\url#1{{\tt #1}}\fi

\bibitem[Cheeseman and Stutz(1995)]{CS95}
P.~Cheeseman and J.~Stutz.
\newblock Bayesian classification {(AutoClass)}: {T}heory and results.
\newblock In U.~Fayyad, G.~Piatesky-Shapiro, P.~Smyth, and R.~Uthurusamy,
  editors, {\em Advances in Knowledge Discovery and Data Mining}, pages
  153--180. AAAI Press, Menlo Park, CA, 1995.

\bibitem[Cooper and Herskovits(1992)]{CH92}
G.~Cooper and E.~Herskovits.
\newblock A {Bayesian} method for the induction of probabilistic networks from
  data.
\newblock {\em Machine Learning}, 9:\penalty0 309--347, 1992.

\bibitem[Dempster et~al.(1977)Dempster, Laird, and Rubin]{DLR77}
A.~Dempster, N.~Laird, and D.~Rubin.
\newblock Maximum likelihood from incomplete data via the {EM} algorithm.
\newblock {\em Journal of the Royal Statistical Society}, B 39:\penalty0 1--38,
  1977.

\bibitem[Domingos and Hulten(2001)]{DH01}
P.~Domingos and G.~Hulten.
\newblock A general method for scaling up machine learning algorithms and its
  application to clustering.
\newblock In {\em Proceedings of the Eighteenth International Conference on
  Machine Learning}, pages 106--113. Morgan Kaufmann, San Mateo, CA, 2001.

\bibitem[Howard()]{Howard66}
R.A. Howard.
\newblock Decision analysis: Applied decision theory.
\newblock In D.B. Hertz and J.~Melese, editors, {\em Proceedings of the Fourth
  International Conference on Operational Research, {\rm Cambridge, MA}}, pages
  55--71. International Federation of Operational Research Societies, 1966.

\bibitem[John and Langley(1996)]{John96}
G.~John and P.~Langley.
\newblock Static versus dynamic sampling for data mining.
\newblock In {\em Proceedings of the Second International Conference on
  Knowledge Discovery and Data Mining}, pages 367--370. AAAI Press, 1996.

\bibitem[Kadie(1995)]{Kadie95}
C.~Kadie.
\newblock {\em Seer: Maximum Likelihood Regression for Learning-Speed Curves}.
\newblock PhD thesis, Department of Computer Science, University of Illinois,
  Urbana, IL, August 1995.

\bibitem[McLachlan and Basford(1988)]{MB88}
G.~McLachlan and K.~Basford.
\newblock {\em Mixture Models: {I}nference and Applications to Clustering}.
\newblock Marcel Dekker, 1988.

\bibitem[Pearce(1983)]{Pearce83}
D.~Pearce.
\newblock {\em Cost-benefit analysis}.
\newblock Macmillan, New York, 1983.

\bibitem[Provost et~al.(1999)Provost, Jensen, and Oates]{Provost99}
F.~Provost, D.~Jensen, and T.~Oates.
\newblock Efficient progressive sampling.
\newblock In {\em Proceedings of the Fifth International Conference on
  Knowledge Discovery and Data Mining}, pages 23--32. ACM, 1999.

\bibitem[Thiesson et~al.(1999)Thiesson, Meek, Chickering, and
  Heckerman]{TMCH99}
B.~Thiesson, C.~Meek, D.~Chickering, and D.~Heckerman.
\newblock Computationally efficient methods for selecting among mixtures of
  graphical models, with discussion.
\newblock In {\em Bayesian Statistics 6: Proceedings of the Sixth Valencia
  International Meeting}, pages 631--656. Clarendon Press, Oxford, 1999.

\bibitem[Titterington et~al.(1985)Titterington, Smith, and Makov]{TSM85}
D.M. Titterington, A.F.M. Smith, and U.E. Makov.
\newblock {\em Statistical analysis of finite mixture distributions}.
\newblock John Wiley and Sons, 1985.

\end{thebibliography}
