-
Chapter and Conference Paper
Penalized Model-Based Clustering with Group-Dependent Shrinkage Estimation
Gaussian mixture models (GMM) are the most-widely employed approach to perform model-based clustering of continuous features. Grievously, with the increasing availability of high-dimensional datasets, their di...
-
Article
Open AccessGroup-Wise Shrinkage Estimation in Penalized Model-Based Clustering
Finite Gaussian mixture models provide a powerful and widely employed probabilistic approach for clustering multivariate continuous data. However, the practical usefulness of these models is jeopardized in hig...
-
Article
Open AccessNonparametric semi-supervised classification with application to signal detection in high energy physics
Model-independent searches in particle physics aim at completing our knowledge of the universe by looking for new possible particles not predicted by the current theories. Such particles, referred to as signal, a...
-
Article
Open AccessCo-clustering of Time-Dependent Data via the Shape Invariant Model
Multivariate time-dependent data, where multiple features are observed over time for a set of individuals, are increasingly widespread in many application domains. To model these data, we need to account for r...
-
Article
Open AccessBetter than the best? Answers via model ensemble in density-based clustering
With the recent growth in data availability and complexity, and the associated outburst of elaborate modelling approaches, model selection tools have become a lifeline, providing objective criteria to deal wit...
-
Chapter and Conference Paper
Three Testing Perspectives on Connectome Data
Guided by an application in the analysis of Magnetic Resonance Imaging (MRI) scans from the neuroimaging realm, we provide some perspectives on statistical techniques that are able to address issues commonly e...
