3 papers
stat.ML2019
Data segmentation based on the local intrinsic dimension
Michele Allegra, Elena Facco, Francesco Denti +2
One of the founding paradigms of machine learning is that a small number of variables is often sufficient to describe high-dimensional data. The minimum number of variables require…
stat.ML2018
Estimating the intrinsic dimension of datasets by a minimal neighborhood information
Elena Facco, Maria d'Errico, Alex Rodriguez +1
Analyzing large volumes of high-dimensional data is an issue of fundamental importance in data science, molecular simulations and beyond. Several approaches work on the assumption…
stat.ML2018
Automatic topography of high-dimensional data sets by non-parametric Density Peak clustering
Maria d'Errico, Elena Facco, Alessandro Laio +1
Data analysis in high-dimensional spaces aims at obtaining a synthetic description of a data set, revealing its main structure and its salient features. We here introduce an approa…