Antoine Godichon

most citedEstimating the geometric median in Hilbert spaces with stochastic gradient algorithms:

L^{p}

and almost sure rates of convergence

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

math.ST2019

An efficient stochastic Newton algorithm for parameter estimation in logistic regressions

Bernard Bercu, Antoine Godichon-Baggioni, Bruno Portier

Logistic regression is a well-known statistical model which is commonly used in the situation where the output is a binary random variable. It has a wide range of applications incl…

math.ST2015★ 5 cited

Estimating the geometric median in Hilbert spaces with stochastic gradient algorithms: $L^{p}$ and almost sure rates of convergence

Antoine Godichon

The geometric median, also called $L^{1}$ -median, is often used in robust statistics. Moreover, it is more and more usual to deal with large samples taking values in high dimension…

An efficient stochastic Newton algorithm for parameter estimation in logistic regressions

Estimating the geometric median in Hilbert spaces with stochastic gradient algorithms: Lp and almost sure rates of convergence

Estimating the geometric median in Hilbert spaces with stochastic gradient algorithms: $L^{p}$ and almost sure rates of convergence