2 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
Penalized deep neural networks estimator with general loss functions under weak dependence
William Kengne, Modou Wade
This paper carries out sparse-penalized deep neural networks predictors for learning weakly dependent processes, with a broad class of loss functions. We deal with a general framew…
Sparse-penalized deep neural networks estimator under weak dependence
William Kengne, Modou Wade
We consider the nonparametric regression and the classification problems for -weakly dependent processes. This weak dependence structure is more general than conditions such as,…
Excess risk bound for deep learning under weak dependence
William Kengne
This paper considers deep neural networks for learning weakly dependent processes in a general framework that includes, for instance, regression estimation, time series prediction,…
Deep learning for -weakly dependent processes
William Kengne, Wade Modou
In this paper, we perform deep neural networks for learning -weakly dependent processes. Such weak-dependence property includes a class of weak dependence conditions such as mix…