1 citations · 2 across the 4 of their papers we have counts for
5 papers
Copula-Based Clustering of Financial Time Series via Evidence Accumulation
Andrea Mecchina, Roberta Pappadà, Nicola Torelli
Understanding the dependence structure of asset returns is fundamental in risk assessment and is particularly relevant in a portfolio diversification strategy. We propose a cluster…
Discrimination in machine learning algorithms
Roberta Pappadà, Francesco Pauli
Machine learning algorithms are routinely used for business decisions that may directly affect individuals, for example, because a credit scoring algorithm refuses them a loan. It…
pivmet: Pivotal Methods for Bayesian Relabelling and k-Means Clustering
Leonardo Egidi, Roberta Pappadà, Francesco Pauli +1
The identification of groups' prototypes, i.e. elements of a dataset that represent different groups of data points, may be relevant to the tasks of clustering, classification and…
Maxima Units Search (MUS) algorithm: methodology and applications
Leonardo Egidi, Roberta Pappadà, Francesco Pauli +1
An algorithm for extracting identity submatrices of small rank and pivotal units from large and sparse matrices is proposed. The procedure has already been satisfactorily applied f…
Relabelling in Bayesian mixture models by pivotal units
Leonardo Egidi, Roberta Pappadà, Francesco Pauli +1
In this paper a simple procedure to deal with label switching when exploring complex posterior distributions by MCMC algorithms is proposed. Although it cannot be generalized to an…