6 papers
Large factor model estimation by nuclear norm plus norm penalization
Matteo Farnè, Angela Montanari
This paper provides a comprehensive estimation framework via nuclear norm plus norm penalization for high-dimensional approximate factor models with a sparse residual covaria…
Matrix sketching for supervised classification with imbalanced classes
Roberta Falcone, Angela Montanari, Laura Anderlucci
Matrix sketching is a recently developed data compression technique. An input matrix A is efficiently approximated with a smaller matrix B, so that B preserves most of the properti…
High-dimensional clustering via Random Projections
Laura Anderlucci, Francesca Fortunato, Angela Montanari
In this work, we address the unsupervised classification issue by exploiting the general idea of Random Projection Ensemble. Specifically, we propose to generate a set of low dimen…
One-class classification with application to forensic analysis
Laura Anderlucci, Francesca Fortunato, Angela Montanari
The analysis of broken glass is forensically important to reconstruct the events of a criminal act. In particular, the comparison between the glass fragments found on a suspect (re…
A bootstrap test to detect prominent Granger-causalities across frequencies
Matteo Farné, Angela Montanari
Granger-causality in the frequency domain is an emerging tool to analyze the causal relationship between two time series. We propose a bootstrap test on unconditional and condition…
The Importance of Being Clustered: Uncluttering the Trends of Statistics from 1970 to 2015
Laura Anderlucci, Angela Montanari, Cinzia Viroli
In this paper we retrace the recent history of statistics by analyzing all the papers published in five prestigious statistical journals since 1970, namely: Annals of Statistics, B…