188 citations · 273 across the 20 of their papers we have counts for
21 papers
Multi-Model Subset Selection
Anthony-Alexander Christidis, Stefan Van Aelst, Ruben Zamar
The two primary approaches for high-dimensional regression problems are sparse methods (e.g., best subset selection, which uses the L0-norm in the penalty) and ensemble methods (e.…
Robust graphical lasso based on multivariate Winsorization
Ginette Lafit, Francisco Nogales, Marcelo Ruiz +1
We propose the use of a robust covariance estimator based on multivariate Winsorization in the context of the Tarr-Muller-Weber framework for sparse estimation of the precision mat…
Data-Driven Logistic Regression Ensembles With Applications in Genomics
Anthony-Alexander Christidis, Stefan Van Aelst, Ruben Zamar
Advances in data collecting technologies in genomics have significantly increased the need for tools designed to study the genetic basis of many diseases. Effective statistical met…
Robust Model-Based Clustering
Juan D. Gonzalez, Ricardo Maronna, Victor J. Yohai +1
We propose a new class of robust and Fisher-consistent estimators for mixture models. These estimators can be used to construct robust model-based clustering procedures. We study i…
Regularized K-means through hard-thresholding
Jakob Raymaekers, Ruben H. Zamar
We study a framework of regularized -means methods based on direct penalization of the size of the cluster centers. Different penalization strategies are considered and compared…
Pooled variable scaling for cluster analysis
Jakob Raymaekers, Ruben H. Zamar
We propose a new approach for scaling prior to cluster analysis based on the concept of pooled variance. Unlike available scaling procedures such as the standard deviation and the…