A large-sample theory for infinitesimal gradient boosting

Author:

Dombry Clément1,Duchamps Jean-Jil1

Affiliation:

1. Université de Franche-Comté, CNRS, LmB, F-25000 Besançon, France

Publisher

Bernoulli Society for Mathematical Statistics and Probability

Reference18 articles.

1. Breiman, L., Friedman, J.H., Olshen, R.A. and Stone, C.J. (1984). Classification and Regression Trees. Wadsworth Statistics/Probability Series. Belmont, CA: Wadsworth Advanced Books and Software.

2. van der Vaart, A.W. and Wellner, J.A. (1996). Weak Convergence and Empirical Processes: With applications to statistics. Springer Series in Statistics. New York: Springer. 10.1007/978-1-4757-2545-2

3. Durrett, R. (2010). Probability: Theory and Examples, 4th ed. Cambridge Series in Statistical and Probabilistic Mathematics 31. Cambridge: Cambridge Univ. Press. 10.1017/CBO9780511779398

4. Hastie, T., Tibshirani, R. and Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd ed. Springer Series in Statistics. New York: Springer. 10.1007/978-0-387-84858-7

5. Scornet, E., Biau, G. and Vert, J.-P. (2015). Consistency of random forests. Ann. Statist. 43 1716–1741. 10.1214/15-AOS1321

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