Team classic

Members
Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities
Dissemination
Bibliography

Bibliography

Major publications by the team in recent years

[1]
K. Bertin, E. Le Pennec, V. Rivoirard.
Adaptive Dantzig density estimation, in: Annales de l'Institut Henri-Poincaré, 2011, to appear.
[2]
G. Biau, L. Devroye, G. Lugosi.
Consistency of random forests and other averaging classifiers, in: Journal of Machine Learning Research, 2008, vol. 9, p. 2015–2033.
[3]
G. Biau, L. Devroye, G. Lugosi.
On the performance of clustering in Hilbert spaces, in: IEEE Transactions on Information Theory, 2008, vol. 54, p. 781–790.
[4]
O. Catoni.
Statistical Learning Theory and Stochastic Optimization — Lectures on Probability Theory and Statistics, École d'Été de Probabilités de Saint-Flour XXXI – 2001, Lecture Notes in Mathematics, Springer, 2004, vol. 1851, 269 pages.
[5]
O. Catoni.
PAC-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning, IMS Lecture Notes Monograph Series, Institute of Mathematical Statistics, 2007, vol. 56, 163 pages.
http://dx.doi.org/10.1214/074921707000000391
[6]
G. Lugosi, S. Mannor, G. Stoltz.
Strategies for prediction under imperfect monitoring, in: Mathematics of Operations Research, 2008, vol. 33, p. 513–528.
[7]
B. Mauricette, V. Mallet, G. Stoltz.
Ozone ensemble forecast with machine learning algorithms, in: Journal of Geophysical Research, 2009, vol. 114, D05307 p.
http://dx.doi.org/10.1029/2008JD009978
[8]
V. Rivoirard, G. Stoltz.
Statistique en action, Vuibert, 2009, Main volume contains 320 pages, supplementary material of 220 pages is available for free download.

Publications of the year

Articles in International Peer-Reviewed Journal

[9]
G. Biau, K. Bleakley, L. Györfi, G. Ottucsák.
Nonparametric sequential prediction of time series, in: Journal of Nonparametric Statistics, 2010, vol. 22, p. 297-317.
[10]
G. Biau, F. Cérou, A. Guyader.
On the rate of convergence of the bagged nearest neighbor estimate, in: Journal of Machine Learning Research, 2010, vol. 11, p. 687-712.
[11]
G. Biau, F. Cérou, A. Guyader.
Rates of convergence of the functional k -nearest neighbor estimate, in: IEEE Transactions on Information Theory, 2010, vol. 56, p. 2034-2040.
[12]
G. Biau, B. Cadre, L. Rouvière.
Statistical analysis of k -nearest neighbor collaborative recommendation, in: The Annals of Statistics, 2010, vol. 38, p. 1568-1592.
[13]
G. Biau, L. Devroye.
On the layered nearest neighbour estimate, the bagged nearest neighbour estimate and the random forest method in regression and classification, in: Journal of Multivariate Analysis, 2010, vol. 101, p. 2499-2518.
[14]
G. Biau, B. Patra.
Sequential quantile prediction of time series, in: IEEE Transactions on Information Theory, 2010, to appear.
[15]
S. Bubeck, R. Munos, G. Stoltz.
Pure Exploration in Finitely-Armed and Continuous-Armed Bandit Problems, in: Theoretical Computer Science, 2010, to appear.
[16]
S. Mannor, G. Stoltz.
A geometric proof of calibration, in: Mathematics of Operations Research, 2010, to appear.

Articles in National Peer-Reviewed Journal

[17]
G. Stoltz.
Agrégation séquentielle de prédicteurs : méthodologie générale et applications à la prévision de la qualité de l'air et à celle de la consommation électrique, in: Journal de la Société Française de Statistique, 2010, vol. 2, no 151.

Other Publications

[18]
J.-Y. Audibert, O. Catoni.
Robust linear least squares regression, 2010.
http://hal.inria.fr/hal-00522534
[19]
J.-Y. Audibert, O. Catoni.
Robust linear regression through PAC-Bayesian truncation, 2010.
http://hal.inria.fr/hal-00522536
[20]
G. Biau.
Analysis of a random forests model, 2010.
http://hal.inria.fr/hal-00476545
[21]
G. Biau, A. Mas.
PCA-Kernel estimation, 2010.
http://hal.inria.fr/hal-00467013
[22]
O. Catoni.
Challenging the empirical mean and empirical variance: a deviation study, 2010.
http://hal.inria.fr/hal-00517206
[23]
M. Devaine, Y. Goude, G. Stoltz.
Forecasting of the electricity consumption by aggregation of specialized experts; application to Slovakian and French country-wide hourly predictions, 2010.
http://hal.archives-ouvertes.fr/hal-00484940
[24]
S. Gerchinovitz.
Sparsity regret bounds for individual sequences in online linear regression, 2010.
http://www.math.ens.fr/~gerchino
[25]
T. Michalski, G. Stoltz.
Do countries falsify economic data strategically? Some evidence that they might do., 2010.
http://halshs.archives-ouvertes.fr/halshs-00482106

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