42 citations · 84 across the 3 of their papers we have counts for
4 papers
All Sparse PCA Models Are Wrong, But Some Are Useful. Part I: Computation of Scores, Residuals and Explained Variance
J. Camacho, A. K. Smilde, E. Saccenti +1
Sparse Principal Component Analysis (sPCA) is a popular matrix factorization approach based on Principal Component Analysis (PCA) that combines variance maximization and sparsity w…
Cross-product Penalized Component Analysis (XCAN)
José Camacho, Evrim Acar, Morten A. Rasmussen +1
Matrix factorization methods are extensively employed to understand complex data. In this paper, we introduce the cross-product penalized component analysis (XCAN), a sparse matrix…
Multivariate Big Data Analysis for Intrusion Detection: 5 steps from the haystack to the needle
José Camacho, José Manuel García-Giménez, Noemí Marta Fuentes-García +1
The research literature on cybersecurity incident detection & response is very rich in automatic detection methodologies, in particular those based on the anomaly detection paradig…
On the Feasibility of Distinguishing Between Process Disturbances and Intrusions in Process Control Systems Using Multivariate Statistical Process Control
Mikel Iturbe, José Camacho, Iñaki Garitano +2
Process Control Systems (PCSs) are the operating core of Critical Infrastructures (CIs). As such, anomaly detection has been an active research field to ensure CI normal operation.…