7 citations · 13 across the 9 of their papers we have counts for
9 papers
TruKAN: Towards More Efficient Kolmogorov-Arnold Networks Using Truncated Power Functions
Ali Bayeh, Samira Sadaoui, Malek Mouhoub
To address the trade-off between computational efficiency and adherence to Kolmogorov-Arnold Network (KAN) principles, we propose TruKAN, a new architecture based on the KAN struct…
Constrained Optimization with Qualitative Preferences
Sultan Ahmed, Malek Mouhoub
The Conditional Preference Network (CP-net) graphically represents user's qualitative and conditional preference statements under the ceteris paribus interpretation. The constraine…
Exact Learning of Qualitative Constraint Networks from Membership Queries
Malek Mouhoub, Hamad Al Marri, Eisa Alanazi
A Qualitative Constraint Network (QCN) is a constraint graph for representing problems under qualitative temporal and spatial relations, among others. More formally, a QCN includes…
An Ontology-Based Information Extraction System for Residential Land Use Suitability Analysis
Munira Al-Ageili, Malek Mouhoub
We propose an Ontology-Based Information Extraction (OBIE) system to automate the extraction of the criteria and values applied in Land Use Suitability Analysis (LUSA) from bylaw a…
Optimizing Neural Network Weights using Nature-Inspired Algorithms
Wael Korani, Malek Mouhoub, Samira Sadaoui
This study aims to optimize Deep Feedforward Neural Networks (DFNNs) training using nature-inspired optimization algorithms, such as PSO, MTO, and its variant called MTOCL. We show…
Communication Aid for Non-English Speaking Newcomers
Munira Al-Ageili, Malek Mouhoub
This research work is intended to assess the usability of Pictogram symbols and other visual symbols in an audio-visual strategy to facilitate and enhance the use and learning of E…
Effect of Word Embedding Models on Hate and Offensive Speech Detection
Safa Alsafari, Samira Sadaoui, Malek Mouhoub
Deep neural networks have been adopted successfully in hate speech detection problems. Nevertheless, the effect of the word embedding models on the neural network's performance has…
The Complexity of Learning Acyclic Conditional Preference Networks
Eisa Alanazi, Malek Mouhoub, Sandra Zilles
Learning of user preferences, as represented by, for example, Conditional Preference Networks (CP-nets), has become a core issue in AI research. Recent studies investigate learning…
A New Approach to Constraint Weight Learning for Variable Ordering in CSPs
Muhammad Rezaul Karim
A Constraint Satisfaction Problem (CSP) is a framework used for modeling and solving constrained problems. Tree-search algorithms like backtracking try to construct a solution to a…