Khalil El Hindi is a professor, at the Department of Computer Science, King Saud University. His main research interests include machine learning, classification algorithms, outlier detection, instance weighing, ensembles of classifiers, similarity distance metrics, and Neural Networks.
The problem of dealing with noisy data in neural network-based models has been receiving more attention by researchers with the aim of mitigating possible consequences on learning. Several methods…
Text classification has many applications in text processing and information retrieval. Instance-based learning (IBL) is among the top-performing text classification methods. However, its…
Analyzing social data as a participatory sensing system (PSS) provides a deep understanding of city dynamics, such as people’s mobility patterns, social patterns, and events detection. In a PSS,…