25 citations · 40 across the 11 of their papers we have counts for
11 papers
Cluster-weighted modeling of lifetime hierarchical data for profiling COVID-19 heart failure patients
Luca Caldera, Andrea Cappozzo, Chiara Masci +5
This study investigates the heterogeneity in survival times among COVID-19 patients with Heart Failure (HF) hospitalized in the Lombardy region of Italy during the pandemic. To add…
Analysis of Higher Education Dropouts Dynamics through Multilevel Functional Decomposition of Recurrent Events in Counting Processes
Alessandra Ragni, Chiara Masci, Anna Maria Paganoni
This paper analyzes the dynamics of higher education dropouts through an innovative approach that integrates recurrent events modeling and point process theory with functional data…
Urban mobility and learning: analyzing the influence of commuting time on students' GPA at Politecnico di Milano
Arianna Burzacchi, Lidia Rossi, Tommaso Agasisti +2
Despite its crucial role in students' daily lives, commuting time remains an underexplored dimension in higher education research. To address this gap, this study focuses on challe…
Clustering Hierarchies via a Semi-Parametric Generalized Linear Mixed Model: a statistical significance-based approach
Alessandra Ragni, Chiara Masci, Francesca Ieva +1
We introduce a novel statistical significance-based approach for clustering hierarchical data using semi-parametric linear mixed-effects models designed for responses with laws in…
Feature Selection for Imbalanced Data with Deep Sparse Autoencoders Ensemble
Michela C. Massi, Francesca Ieva, Francesca Gasperoni +1
Class imbalance is a common issue in many domain applications of learning algorithms. Oftentimes, in the same domains it is much more relevant to correctly classify and profile min…
Learning High-Order Interactions via Targeted Pattern Search
Michela C. Massi, Nicola R. Franco, Francesca Ieva +3
Logistic Regression (LR) is a widely used statistical method in empirical binary classification studies. However, real-life scenarios oftentimes share complexities that prevent fro…