resume_these_fr.bbl

\begin{thebibliography}{61}
\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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Y.~Amit and D.~Geman.
\newblock Shape quantization and recognition with randomized trees.
\newblock {\em Neural Comput.}, 9:\penalty0 1545--1588, 1997.

\bibitem[Baillo(2003)]{Baillo2003}
A.~Baillo.
\newblock Total error in a plug-in estimator of level sets.
\newblock {\em Statistics \& probability letters}, 65:\penalty0 411--417, 2003.

\bibitem[Baillo et~al.(2001)Baillo, Cuesta-Albertos, and Cuevas]{Baillo2001}
A.~Baillo, J.~A Cuesta-Albertos, and A.~Cuevas.
\newblock Convergence rates in nonparametric estimation of level sets.
\newblock {\em Statistics \& probability letters}, 53:\penalty0 27--35, 2001.

\bibitem[Biau et~al.(2008)Biau, Devroye, and Lugosi]{Biau2008}
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\newblock Consistency of random forests and other averaging classifiers.
\newblock {\em JMLR}, 9:\penalty0 2015--2033, 2008.

\bibitem[Biau \& Scornet(2016)Biau and Scornet]{Biau2016}
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\newblock A random forest guided tour.
\newblock {\em Test}, 25:\penalty0 197--227, 2016.

\bibitem[Breiman(2001)]{Breiman2001}
L.~Breiman.
\newblock Random forests.
\newblock {\em Machine learning}, 45:\penalty0 5--32, 2001.

\bibitem[Cadre(2006)]{Cadre2006}
B.~Cadre.
\newblock Kernel estimation of density level sets.
\newblock {\em JMVA}, 97:\penalty0 999--1023, 2006.

\bibitem[Cl\'emen\c{c}on \& Jakubowicz(2013)Cl\'emen\c{c}on and
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S.~Cl\'emen\c{c}on and J.~Jakubowicz.
\newblock Scoring anomalies: a m-estimation formulation.
\newblock In {\em Proc. AISTATS}, volume~13, pages 659--667, 2013.

\bibitem[Cl\'emen\c{c}on \& Robbiano(2014)Cl\'emen\c{c}on and Robbiano]{CLEM14}
S.~Cl\'emen\c{c}on and S.~Robbiano.
\newblock {Anomaly Ranking as Supervised Bipartite Ranking}.
\newblock In {\em Proc. ICML}, 2014.

\bibitem[Cl{\'e}men{\c{c}}on \& Vayatis(2009)Cl{\'e}men{\c{c}}on and
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S.~Cl{\'e}men{\c{c}}on and N.~Vayatis.
\newblock Nonparametric estimation of the precision-recall curve.
\newblock In {\em Proc. ICML}, pages 185--192, 2009.

\bibitem[Cl{\'e}men{\c{c}}on \& Vayatis(2010)Cl{\'e}men{\c{c}}on and
  Vayatis]{Clemencon2010}
S.~Cl{\'e}men{\c{c}}on and N.~Vayatis.
\newblock Overlaying classifiers: a practical approach to optimal scoring.
\newblock {\em Constr Approx}, 32:\penalty0 619--648, 2010.

\bibitem[Clifton et~al.(2011)Clifton, Hugueny, and Tarassenko]{Clifton2011}
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\newblock Novelty detection with multivariate extreme value statistics.
\newblock {\em J Signal Process Syst.}, 65:\penalty0 371--389, 2011.

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\newblock Bayesian extreme value statistics for novelty detection in
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\newblock In {\em AEROSP CONF PROC}, pages 1--11, 2008.

\bibitem[Coles \& Tawn(1991)Coles and Tawn]{coles1991modeling}
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\newblock Modeling extreme multivariate events.
\newblock {\em JR Statist. Soc. B}, 53:\penalty0 377--392, 1991.

\bibitem[Cooley et~al.(2010)Cooley, Davis, and Naveau]{cooley2010pairwise}
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\newblock The pairwise beta distribution: A flexible parametric multivariate
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\newblock {\em JMVA}, 101:\penalty0 2103--2117, 2010.

\bibitem[Cuevas \& Fraiman(1997)Cuevas and Fraiman]{Cuevas1997}
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\newblock A plug-in approach to support estimation.
\newblock {\em Ann. Stat.}, pages 2300--2312, 1997.

\bibitem[Davis \& Goadrich(2006)Davis and Goadrich]{Davis2006}
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\newblock The relationship between precision-recall and roc curves.
\newblock In {\em Proc. ICML}, 2006.

\bibitem[De~Haan \& Ferreira(2007)De~Haan and Ferreira]{dHF06}
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\newblock {\em Extreme value theory: an introduction}.
\newblock Springer Science \& Business Media, 2007.

\bibitem[Drees \& Huang(1998)Drees and Huang]{Drees98}
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\newblock Best attainable rates of convergence for estimators of the stable
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\newblock {\em JMVA}, 64:\penalty0 25--47, 1998.

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\newblock A new random forest method for one-class classification.
\newblock In {\em Structural, Syntactic, and Statistical Pattern Recognition}.
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\bibitem[Einmahl et~al.(2012)Einmahl, Krajina, and Segers]{Einmahl2012}
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\newblock An m-estimator for tail dependence in arbitrary dimensions.
\newblock {\em Ann. Stat.}, 40:\penalty0 1764--1793, 2012.

\bibitem[Einmahl \& Segers(2009)Einmahl and Segers]{Einmahl2009}
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\newblock Maximum empirical likelihood estimation of the spectral measure of an
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\newblock {\em Ann. Stat.}, 37:\penalty0 2953--2989, 2009.

\bibitem[Einmahl et~al.(2001)Einmahl, de~Haan, and Piterbarg]{Einmahl2001}
J.~HJ Einmahl, L.~de~Haan, and V.~I Piterbarg.
\newblock Nonparametric estimation of the spectral measure of an extreme value
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\newblock {\em Ann. Stat.}, 29:\penalty0 1401--1423, 2001.

\bibitem[Einmahl \& Mason(1992)Einmahl and Mason]{Einmahl1992}
J.~HJ Einmahl and D.~M Mason.
\newblock Generalized quantile processes.
\newblock {\em Ann. Stat.}, 20:\penalty0 1062--1078, 1992.

\bibitem[Embrechts et~al.(2000)Embrechts, de~Haan, and Huang]{Embrechts2000}
P.~Embrechts, L.~de~Haan, and X.~Huang.
\newblock Modelling multivariate extremes.
\newblock {\em Extremes and integrated risk management}, pages 59--67, 2000.

\bibitem[Fawcett(2006)]{Fawcett2006}
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\newblock An introduction to roc analysis.
\newblock {\em Pattern recognition letters}, 27:\penalty0 861--874, 2006.

\bibitem[Foug{\`e}res et~al.(2009)Foug{\`e}res, Nolan, and
  Rootz{\'e}n]{fougeres2009models}
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\newblock Models for dependent extremes using stable mixtures.
\newblock {\em Scandinavian Journal of Statistics}, 36:\penalty0 42--59, 2009.

\bibitem[Genuer et~al.(2008)Genuer, Poggi, and Tuleau]{Genuer2008}
R.~Genuer, J.-M. Poggi, and C.~Tuleau.
\newblock Random forests: some methodological insights.
\newblock {\em arXiv:0811.3619}, 2008.

\bibitem[Gini(1912)]{Gini1912}
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\newblock Variabilita e mutabilita.
\newblock {\em Memorie di metodologia statistica}, 1912.

\bibitem[Goix(2016)]{ICMLworkshop16}
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\newblock {How to Evaluate the Quality of Unsupervised Anomaly Detection
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\newblock In {\em ICML Workshop on Anomaly Detection}, 2016.

\bibitem[Goix et~al.(2016{\natexlab{a}})Goix, Brault, Drougard, and
  Chiapino]{OCRF16}
N.~Goix, R.~Brault, N.~Drougard, and M.~Chiapino.
\newblock {One Class Splitting Criteria for Random Forests with Application to
  Anomaly Detection}.
\newblock Submitted to AISTATS, 2016{\natexlab{a}}.

\bibitem[Goix et~al.(2015{\natexlab{a}})Goix, Sabourin, and Cl{\'e}men{\c
  c}on]{NIPSWORKSHOP15}
N.~Goix, A.~Sabourin, and S.~Cl{\'e}men{\c c}on.
\newblock {Sparse Representation of Multivariate Extremes}.
\newblock NIPS 2015 Workshop on Nonparametric Methods for Large Scale
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\bibitem[Goix et~al.(2016{\natexlab{b}})Goix, Sabourin, and Cl{\'e}men{\c
  c}on]{ARXIV16}
N.~Goix, A.~Sabourin, and S.~Cl{\'e}men{\c c}on.
\newblock {Sparse Representation of Multivariate Extremes with Applications to
  Anomaly Detection}.
\newblock In the reviewing process of JMVA, July 2016{\natexlab{b}}.

\bibitem[Goix et~al.(2015{\natexlab{b}})Goix, Sabourin, and
  Clémençon]{COLT15}
N.~Goix, A.~Sabourin, and S.~Clémençon.
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\newblock In {\em Proc. AISTATS}, 2015{\natexlab{c}}.

\bibitem[Goix et~al.(2016{\natexlab{c}})Goix, Sabourin, and
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\newblock {Sparse Representation of Multivariate Extremes with Applications to
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\newblock In {\em Proc. AISTATS}, 2016{\natexlab{c}}.

\bibitem[Goix \& Thomas(2016)Goix and Thomas]{NIPS16evaluation}
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\newblock {How to Evaluate the Quality of Unsupervised Anomaly Detection
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\newblock To be submitted, 2016.

\bibitem[Ho(1998)]{Ho1998}
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\newblock The random subspace method for constructing decision forests.
\newblock {\em IEEE transactions on pattern analysis and machine intelligence},
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\bibitem[Huang(1992)]{Huangphd}
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\newblock Statistics of bivariate extreme values.
\newblock {\em PhD thesis}, 1992.

\bibitem[Lee \& Roberts(2008)Lee and Roberts]{Lee2008}
H.J. Lee and S.J. Roberts.
\newblock On-line novelty detection using the kalman filter and extreme value
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\newblock In {\em ICPR}, pages 1--4, 2008.

\bibitem[Liu et~al.(2008)Liu, Ting, and Zhou]{Liu2008}
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\newblock {Isolation Forest}.
\newblock In {\em ICDM}, pages 413--422, 2008.

\bibitem[Mason \& Polonik(2009)Mason and Polonik]{Mason2009}
D.~M. Mason and W.~Polonik.
\newblock Asymptotic normality of plug-in level set estimates.
\newblock {\em The Annals of Applied Probability}, 19:\penalty0 1108--1142,
  2009.

\bibitem[Panov \& D{\v{z}}eroski(2007)Panov and D{\v{z}}eroski]{Panov2007}
P.~Panov and S.~D{\v{z}}eroski.
\newblock {\em Combining bagging and random subspaces to create better
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\newblock Springer, 2007.

\bibitem[Pedregosa et~al.(2011)Pedregosa, Varoquaux, Gramfort, Michel, Thirion,
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\bibitem[Polonik(1995)]{Polonik95}
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\newblock {Measuring Mass Concentrations and Estimating Density Contour
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\newblock {\em Ann. Stat.}, 23:\penalty0 855--881, 1995.

\bibitem[Polonik(1997)]{Polonik97}
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\newblock {Minimum volume sets and generalized quantile processes}.
\newblock {\em Stochastic Processes and their Applications}, 69:\penalty0
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\bibitem[Provost et~al.(1997)Provost, Fawcett, et~al.]{Provost1997}
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\newblock Analysis and visualization of classifier performance: comparison
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\newblock In {\em KDD}, volume~97, pages 43--48, 1997.

\bibitem[Provost et~al.(1998)Provost, Fawcett, and Kohavi]{Provost1998}
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\newblock The case against accuracy estimation for comparing induction
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\newblock In {\em Proc. ICML}, volume~98, pages 445--453, 1998.

\bibitem[Qi(1997)]{Qi97}
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\newblock Almost sure convergence of the stable tail empirical dependence
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\newblock {\em Acta Mathematicae Applicatae Sinica}, 13:\penalty0 167--175,
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\bibitem[Rigollet \& Vert(2009)Rigollet and Vert]{Rigollet2009}
P.~Rigollet and R.~Vert.
\newblock Optimal rates for plug-in estimators of density level sets.
\newblock {\em Bernoulli}, 15:\penalty0 1154--1178, 2009.

\bibitem[Roberts(1999)]{Roberts99}
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\newblock Novelty detection using extreme value statistics.
\newblock {\em IEE P-VIS IMAGE SIGN}, 146:\penalty0 124--129, Jun 1999.

\bibitem[Roberts(2000)]{Roberts2000}
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\newblock Extreme value statistics for novelty detection in biomedical data
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\newblock {\em IEE P-SCI MEAS TECH}, 147:\penalty0 363--367, 2000.

\bibitem[Sabourin \& Naveau(2014)Sabourin and Naveau]{sabourinNaveau2012}
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\newblock Bayesian dirichlet mixture model for multivariate extremes: A
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\newblock {\em Comput. Stat. Data Anal.}, 71:\penalty0 542--567, 2014.

\bibitem[Sch{\"o}lkopf et~al.(2001)Sch{\"o}lkopf, Platt, Shawe-Taylor, Smola,
  and Williamson]{Scholkopf2001}
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\newblock Estimating the support of a high-dimensional distribution.
\newblock {\em Neural Comput.}, 13:\penalty0 1443--1471, 2001.

\bibitem[Scott \& Nowak(2006)Scott and Nowak]{Scott2006}
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\newblock Learning minimum volume sets.
\newblock {\em JMLR}, 7:\penalty0 665--704, 2006.

\bibitem[Shi \& Horvath(2012)Shi and Horvath]{Shi2012}
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\newblock Unsupervised learning with random forest predictors.
\newblock {\em J. Comp. Graph. Stat.}, 15, 2012.

\bibitem[Steinwart et~al.(2005)Steinwart, Hush, and Scovel]{Steinwart2005}
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\newblock {\em JMLR}, 6:\penalty0 211--232, 2005.

\bibitem[Stephenson(2009)]{stephenson2009high}
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\newblock {\em Australian \& New Zealand Journal of Statistics}, 51:\penalty0
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\bibitem[Vert \& Vert(2006)Vert and Vert]{VertVert}
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\end{thebibliography}