IEEE

Reinforcement Learning-Based Voting for Feature Drift-Aware Intrusion Detection: An Incremental Learning Framework

Abstract: In Intrusion Detection Systems (IDS), stream data classification faces significant challenges due to concept drifts and feature evolution, where traditional methods struggle to maintain ...
Scientific Research Publishing

De-Risking Returns: How AI Can Reinvent Big Tech’s China-Tied Reverse Supply Chains ()

Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
IEEE

Gram–Schmidt Methods for Unsupervised Feature Extraction and Selection

Abstract: Feature extraction and selection in the presence of nonlinear dependencies among the data is a fundamental challenge in unsupervised learning. We propose using a Gram-Schmidt (GS) type ...