Zobrazeno 1 - 10
of 218
pro vyhledávání: '"WINTENBERGER, OLIVIER"'
We study boosting for adversarial online nonparametric regression with general convex losses. We first introduce a parameter-free online gradient boosting (OGB) algorithm and show that its application to chaining trees achieves minimax optimal regret
Externí odkaz:
http://arxiv.org/abs/2410.03363
This paper investigates predictive probability inference for classification tasks using random forests in the context of imbalanced data. In this setting, we analyze the asymptotic properties of simplified versions of the original Breiman's algorithm
Externí odkaz:
http://arxiv.org/abs/2408.01777
Autor:
Genans, Ferdinand, Godichon-Baggioni, Antoine, Vialard, François-Xavier, Wintenberger, Olivier
Optimal Transport (OT) based distances are powerful tools for machine learning to compare probability measures and manipulate them using OT maps. In this field, a setting of interest is semi-discrete OT, where the source measure $\mu$ is continuous,
Externí odkaz:
http://arxiv.org/abs/2405.14459
We introduce an online mathematical framework for survival analysis, allowing real time adaptation to dynamic environments and censored data. This framework enables the estimation of event time distributions through an optimal second order online con
Externí odkaz:
http://arxiv.org/abs/2402.05145
We study the tail asymptotics of two functionals (the maximum and the sum of the marks) of a generic cluster in two sub-models of the marked Poisson cluster process, namely the renewal Poisson cluster process and the Hawkes process. Under the hypothe
Externí odkaz:
http://arxiv.org/abs/2304.09705
We study the joint limit behavior of sums, maxima and $\ell^p$-type moduli for samples taken from an $\mathbb{R}^d$-valued regularly varying stationary sequence with infinite variance. As a consequence, we can determine the distributional limits for
Externí odkaz:
http://arxiv.org/abs/2303.17221
Electricity load forecasting is a necessary capability for power system operators and electricity market participants. The proliferation of local generation, demand response, and electrification of heat and transport are changing the fundamental driv
Externí odkaz:
http://arxiv.org/abs/2301.10090
Optimistic Online Learning algorithms have been developed to exploit expert advices, assumed optimistically to be always useful. However, it is legitimate to question the relevance of such advices \emph{w.r.t.} the learning information provided by gr
Externí odkaz:
http://arxiv.org/abs/2301.07530
Extremes occur in stationary regularly varying time series as short periods with several large observations, known as extremal blocks. We study cluster statistics summarizing the behavior of functions acting on these extremal blocks. Examples of clus
Externí odkaz:
http://arxiv.org/abs/2212.13521
Publikováno v:
Brazilian Journal of Probability and Statistics Vol. 38, Issue 1, (Mar 2024) , pgs 88-107
We consider random coefficient autoregressive models of infinite order (AR($\infty$)) under the assumption of non-negativity of the coefficients. We develop novel methods yielding sufficient or necessary conditions for finiteness of moments, based on
Externí odkaz:
http://arxiv.org/abs/2207.07069