17 citations · 60 across the 10 of their papers we have counts for
7 papers · 1 filter
One-step ahead sequential Super Learning from short times series of many slightly dependent data, and anticipating the cost of natural disasters
Geoffrey Ecoto, Aurélien Bibaut, Antoine Chambaz
Suppose that we observe a short time series where each time-t-specific data-structure consists of many slightly dependent data indexed by a and that we want to estimate a feature o…
Adaptive Sequential Design for a Single Time-Series
Ivana Malenica, Aurelien Bibaut, Mark J. van der Laan
The current work is motivated by the need for robust statistical methods for precision medicine; as such, we address the need for statistical methods that provide actionable infere…
Sequential causal inference in a single world of connected units
Aurelien Bibaut, Maya Petersen, Nikos Vlassis +2
We consider adaptive designs for a trial involving N individuals that we follow along T time steps. We allow for the variables of one individual to depend on its past and on the pa…
Sufficient and insufficient conditions for the stochastic convergence of Cesàro means
Aurélien F. Bibaut, Alex Luedtke, Mark J. van der Laan
We study the stochastic convergence of the Cesàro mean of a sequence of random variables. These arise naturally in statistical problems that have a sequential component, where the…
Fast rates for empirical risk minimization over càdlàg functions with bounded sectional variation norm
Aurélien F. Bibaut, Mark J. van der Laan
Empirical risk minimization over classes functions that are bounded for some version of the variation norm has a long history, starting with Total Variation Denoising (Rudin et al.…
Uniform Consistency of the Highly Adaptive Lasso Estimator of Infinite Dimensional Parameters
Mark J. van der Laan, Aurélien F. Bibaut
Consider the case that we observe independent and identically distributed copies of a random variable with a probability distribution known to be an element of a specified stat…