67 citations · 161 across the 9 of their papers we have counts for
9 papers
A Recursive Algorithm for Mining Association Rules
Abdelkader Mokkadem, Mariane Pelletier, Louis Raimbault
Mining frequent itemsets and association rules is an essential task within data mining and data analysis. In this paper, we introduce PrefRec, a recursive algorithm for finding fre…
Revisiting Révész's stochastic approximation method for the estimation of a regression function
Abdelkader Mokkadem, Mariane Pelletier, Yousri Slaoui
In a pioneer work, Révész (1973) introduces the stochastic approximation method to build up a recursive kernel estimator of the regression function . However, ac…
The stochastic approximation method for the estimation of a multivariate probability density
Abdelkader Mokkadem, Mariane Pelletier, Yousri Slaoui
We apply the stochastic approximation method to construct a large class of recursive kernel estimators of a probability density, including the one introduced by Hall and Patil (199…
Joint behaviour of semirecursive kernel estimators of the location and of the size of the mode of a probability density function
Abdelkader Mokkadem, Mariane Pelletier, Baba Thiam
Let and denote the location and the size of the mode of a probability density. We study the joint convergence rates of semirecursive kernel estimators of and . We sh…
Large and moderate deviations principles for kernel estimators of the multivariate regression
Abdelkader Mokkadem, Mariane Pelletier, Baba Thiam
In this paper, we prove large deviations principle for the Nadaraya-Watson estimator and for the semi-recursive kernel estimator of the regression in the multidimensional case. Und…
Convergence rate and averaging of nonlinear two-time-scale stochastic approximation algorithms
Abdelkader Mokkadem, Mariane Pelletier
The first aim of this paper is to establish the weak convergence rate of nonlinear two-time-scale stochastic approximation algorithms. Its second aim is to introduce the averaging…