We propose a vector auto-regressive model with a low-rank constraint on the transition
matrix. This model is well suited to predict high-dimensional series that are highly correlated …

In this paper, we introduce a class of processes that contains many natural examples. The
interesting feature of such type processes lays on its infinite memory that allows it to record a …

Concentration inequalities are widely used for analyzing machine learning algorithms.
However, the current concentration inequalities cannot be applied to some non-causal …

Concentration inequalities are widely used for analyzing machine learning algorithms.
However, current concentration inequalities cannot be applied to some of the most popular …

Let $\left\{Z_ {n}, n\ge 0\right\} $ be a supercritical branching process in an independent and
identically distributed random environment $\xi=\left (\xi _ {n}\right) _ {n\geq 0} $. In this …

We introduce a class of Markov chains that includes models of stochastic approximation by
averaging and non-averaging. Using a martingale approximation method, we establish …

Prédire les futures valeurs de séries temporelles semble pourtant nécessaire dans de
nombreux domaines. On trouve ainsi des applications pour contrôler divers processus …