5 citations · 5 across the 1 of their papers we have counts for
3 papers
Learning Clique Forests
Guido Previde Massara, Tomaso Aste
We propose a topological learning algorithm for the estimation of the conditional dependency structure of large sets of random variables from sparse and noisy data. The algorithm,…
Parsimonious modeling with Information Filtering Networks
Wolfram Barfuss, Guido Previde Massara, T. Di Matteo +1
We introduce a methodology to construct parsimonious probabilistic models. This method makes use of Information Filtering Networks to produce a robust estimate of the global sparse…
Network Filtering for Big Data: Triangulated Maximally Filtered Graph
Guido Previde Massara, T. Di Matteo, Tomaso Aste
We propose a network-filtering method, the Triangulated Maximally Filtered Graph (TMFG), that provides an approximate solution to the Weighted Maximal Planar Graph problem. The und…