1 citations · 1 across the 4 of their papers we have counts for
4 papers
Leave-one-out testing for node-level differences in Gaussian graphical models
Davide Benussi, Ester Alongi, Erika Banzato
We study two-sample equality testing in Gaussian graphical models. Classical likelihood ratio tests on decomposable graphs admit clique-wise factorizations, offering limited locali…
Existence of Direct Density Ratio Estimators
Erika Banzato, Mathias Drton, Kian Saraf-Poor +1
Many two-sample problems call for a comparison of two distributions from an exponential family. Density ratio estimation methods provide ways to solve such problems through direct…
Guided structure learning of DAGs for count data
Thi Kim Hue Nguyen, Monica Chiogna, Davide Risso +1
In this paper, we tackle structure learning of Directed Acyclic Graphs (DAGs), with the idea of exploiting available prior knowledge of the domain at hand to guide the search of th…
Construction and assessment of prediction rules for binary outcome in the presence of missing predictor data using multiple imputation: theoretical perspective and data-based evaluation
B. J. A. Mertens, E. Banzato, L. C. de Wreede
We investigate the problem of calibration and assessment of predictive rules in prognostic designs when missing values are present in the predictors. Our paper has two key objectiv…