1 citations · 2 across the 3 of their papers we have counts for
3 papers
Computing the Vapnik Chervonenkis Dimension for Non-Discrete Settings
Mohammed Nechba, Mouhajir Mohamed, Sedjari Yassine
In 1984, Valiant [ 7 ] introduced the Probably Approximately Correct (PAC) learning framework for boolean function classes. Blumer et al. [ 2] extended this model in 1989 by introd…
High Performance Computing Applied to Logistic Regression: A CPU and GPU Implementation Comparison
Nechba Mohammed, Mouhajir Mohamed, Sedjari Yassine
We present a versatile GPU-based parallel version of Logistic Regression (LR), aiming to address the increasing demand for faster algorithms in binary classification due to large d…
An Introduction to the Hausdorff Measure and Its Applications in Fractal Geometry
Mohammed Nechba, Mustapha Ouyaaz, Abdellatif El Afia +1
This paper presents a comprehensive introduction to the Hausdorff measure, a fundamental tool in fractal geometry and geometric measure theory. We begin by defining the Hausdorff o…