5 papers
Higher order multi-dimension reduction methods via Einstein product
Alaeddine Zahir, Khalide Jbilou, Ahmed Ratnani
This paper explores the extension of dimension reduction (DR) techniques to the multi-dimension case by using the Einstein product. Our focus lies on graph-based methods, encompass…
Trace Ratio vs Ratio Trace Methods for Multidimensional Dimensionality Reduction
Alaeddine Zahir, Franck Dufrenois, Khalide Jbilou +1
We propose a higher-order dimensionality reduction framework based on the Trace Ratio (TR) optimization problem. We establish conditions for existence and uniqueness of solutions a…
High-dimensional multi-view clustering methods
Alaeddine Zahir, Khalide Jbilou, Ahmed Ratnani
Multi-view clustering has been widely used in recent years in comparison to single-view clustering, for clear reasons, as it offers more insights into the data, which has brought w…
Quaternion tensor low rank Quaternion tensor low-rank approximation using a family of non-convex norms
Alaeddine Zahir, Ahmed Ratnani, Khalide Jbilou
In this paper, we propose a new approaches for low rank approximation of quaternion tensors \cite{chen2019low,zhang1997quaternions,hamilton1866elements}. The first method uses quas…
A low-rank non-convex norm method for multiview graph clustering
Alaeddine Zahir, Khalide Jbilou, Ahmed Ratnani
This study introduces a novel technique for multi-view clustering known as the "Consensus Graph-Based Multi-View Clustering Method Using Low-Rank Non-Convex Norm" (CGMVC-NC). Multi…