Peer reviewed articles
Menardi, G., De Stefano, D. (2021+) Density-based clustering of social networks. Journal of the Royal Statistical Society, Series A: Statistics in Society (in press)
Stakia, A., Dorigo, T., Banelli, A., Bortoletto, D., Casa, A., de Castro, P., Delaere, C., Donini, J., Finos, L., Gallinaro, M., Giammanco, A., Held, A., Morales, F. J., Kotkowski, G., Liew, S.P., Maltoni, F., Menardi, G., Papavergou, I. , Saggio, A., Scarpa, B., Strong, G., Tosciri, C., Varela, J., Vischia, P., Weiler, A. (2021+) Advances in multivariate analysis methods for new physics searches at the Large Hadron Collider. Reviews in Physics (In press)
Casa, A., Bouveyron, C., Erosheva, E., Menardi, G. (2021+) Co-clustering of Time-Dependent Data via the Shape Invariant Model. J Classif (2021). https://doi.org/10.1007/s00357-021-09402-8.
Casa, A., Menardi, G. (2021+). Nonparametric semi-supervised classification with application to signal detection in high energy physics. Statistical Methods & Applications. https://doi.org/10.1007/s10260-021-00585-3
Casa A., Scrucca L., Menardi G. (2021) Better than the best? Answers via model ensemble in density-based clustering. Advances in Data Analysis and Classification. 15, 599–623.
Lunardon, N., Menardi G. (2020) Comment on “Wang et al. (2005), Robust Estimating Functions and Bias Correction for Longitudinal Data Analysis”. Biometrics, 76(3), 1040-1042.
Costantin, D., Menardi, G., Brazzale, A.R., Bastieri, D., Fan J.H. (2020) A novel approach for pre-filtering event sources using the von Mises–Fisher distribution. Astrophysics and Space Science, 365 (53).
Casa, A., Chacón, J.E., Menardi, G. (2020) Modal clustering asymptotics with applications to bandwidth selection. Electronic Journal of Statistics, 14(1), 835-856
Menardi, G. (2020) Nonparametric clustering for image segmentation. Statistical Analysis and Data Mining, 13(1), 83-97
Menardi, G. (2016) A review on modal clustering. International Statistical Review. 84(3), 413-433. Azzalini, A.,
Menardi, G. (2016) Density-based clustering with non-continuous data. Computational Statistics. 31, 771-798.
Menardi, G., Lisi, F. (2015) Double clustering for rating mutual funds. Electronic Journal of Applied Statistical Analysis. 8(1), 44-56.
Lunardon, N. Menardi, G. Torelli, N. (2014) ROSE: a package for class imbalance learning, The R Journal, 6(1): 79-89.
Menardi, G., Azzalini. A. (2014). An advancement in clustering via nonparametric density estimation. Statistics and Computing, 24(5): 753-767.
Azzalini, A. Menardi, G. (2014) Clustering via Nonparametric Density Estimation: the R Package pdfCluster. Journal of Statistical Software. 57(11): 1-26.
Menardi, G., Torelli, N. (2014). Training and assessing classification rules with imbalanced data. Data Mining and Knowledge Discovery. 28(1): 92-122.
Menardi, G. Torelli, N. (2013) Effect of training set selection when predicting defaulting small and medium sized enterprises with unbalanced data. Journal of Credit Risk 9(4).
Menardi, G., Torelli, N. (2013). Reducing data dimension for cluster detection. Journal of Statistical Computation and Simulation. 83(11): 2047-2063. Menardi, G. (2013). Multidimensional connected set detection in clustering based on nonparametric density estimation. In: M. Grigoletto, F. Lisi, S. Petrone: Complex Models and Computational Methods in Statistics. Springer/Physica Verlag, Heidelberg.
Menardi, G., Lisi, F. (2012). Are performance measures equally stable? Annals of Finance 4:553- 570.
Menardi, G., Lisi, F. (2012). On the stability of performance measures over time: an empirical study The Journal of Performance Measurement, winter 2011/2012: 36- 45.
Menardi, G. (2011). Density-based silhouette diagnostics for clustering methods Statistics and Computing, 21:295- 308.
Menardi, G., Tedeschi, F., Torelli, N. (2011). On the use of boosting procedures to predict the risk of default. In: Fichet, B., Piccolo, D., Verde, R., Vichi, M. . Classification and Multivariate Analysis for Complex Data Structures. Springer Verlag, 211- 218.
Menardi, G., Torelli, N. (2010). Preserving the clustering structure by a projection pursuit approach. In: F. Palumbo, C.N. Lauro, M.J. Greenacre. Data Analysis and Classification . Springer Verlag, Berlin: 171- 178.
Menardi G; Monte A; Pauli F. (2006). Stima delle Forze di lavoro per le province del Friuli-Venezia Giulia integrando rilevazioni campionarie e fonti amministrative. In: LISEO B; MONTANARI G; TORELLI N. Metodi statistici per l’integrazione di dati da fonti diverse. FrancoAngeli, MILANO: 119- 139.
Conference proceedings
Ferraccioli, F., Menardi, G. (2021). On testing the significance of a mode. Book of Short Papers, SIS 2021 – ISBN 9788891927361.
Menardi, G., Ferraccioli, F. (2021) A nonparametric test for mode significance. Book of short papers, CLADAG 2021 – ISBN 978-88-5518-340-6.
Ferraccioli, F., Menardi, G. (2020) A modal approach for clustering matrices. Book of Short Papers, SIS 2020
Menardi, G., Costantin, D., Ferraccioli, F. (2020). Identification of high-energy γ−ray sources via nonparametric clustering. Book of Short Papers, SIS 2020
Costantin, D., Menardi, G., Brazzale, A.R. (2019) A novel approach for pre-filtering event sources using the von Mises distribution. EMS 2019 Program and Book of Abstracts
Vischia, P., Dorigo, T., Menardi, G., Kotkowski, G. M. (2019) The DAB: detecting anomalies via bootstrapping. EMS 2019 Book and Short Abstracts
Pascali, G., Casa, A., Menardi, G. (2019) Co-clustering TripAdvisor data for personalized recommendations. Book of short papers SIS 2019
Casa, A., Menardi, G. (2019) Nonparametric Semisupervised Classification and Variable Selection for New Physics Searches. EMS 2019 – Program and Book of Abstracts
Casa, A., Chacòn Duran, J.E., Menardi, G (2019) Asymptotics for bandwidth selection in nonparametric clustering. Cladag 2019 – Book of Short Papers
Dossi, M., Menardi, G. (2019) AUC-based gradient boosting for imbalanced classification. Cladag 2019 – Book of Short Papers
Casa, A, Chacon, J., Menardi, G. (2018) On the choice of an appropriate bandwidth for modal clustering. Proceedings of the 49th Scientific meeting of the Italian Statistical Society, Palermo.
Casa, A, Chacon, J., Menardi, G. (2018) Clustering-oriented selection of the amount of smoothing in kernel density estimation. Book of abstracts, ISNPS 2018 4th Conference of the International Society for Nonparametric Statistics, Salerno.
Kotkowski, G., Finos, L., Menardi, G., Scarpa, B. (2018). Model independent searches for new physics via parametric anomaly detection. XIIIth Quark Confinement and the Hadron Spectrum Conference, Maynooth University, Dublin, Ireland, 01-03.08.2018.
Casa, A., Scrucca. L. Menardi, G. (2018) On the selection uncertainty in parametric clustering. Book of Abstracts, ECDA 2018 European Conference on Data Analysis, Paderborn.
Casa, A., Menardi, G. (2017) Nonparametric semi-supervised classification with application to signal detection in high energy physics. Book of Abstracts of the International federation of the Classification Societies (IFCS). Tokyo.
De Castro Manzano, P., Dall’Osso, M., Dorigo, T., Finos, L., Kotkowski, G., Menardi, G., Scarpa, B. (2017) Hemisphere mixing. A fully data-driven model of QCD multijet backgrounds for LHC searches. Proceedings of Sciences – the European Physical Society of High Energy Physics.
Casa, A., Menardi, G. (2017) Signal detection in high energy physics via a semisupervised nonparametric approach. Proceedings of the Conference of the Italian Statistical Society “Statistics and data Sciences: new challenges, new generations”. Firenze. ISBN: 978-88-6453-521-0.
Menardi, G. (2016) Stability-based model selection in nonparametric clustering. Proceedings of the 48th SIS Scientific Meeting of the Italian Statistical Society. Salerno, ISBN: 978-88-619-7061-8.
Menardi, G. (2015) A Nonparametric Clustering Method for Image Segmentation. Proceedings of the 10th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (Invited papers). Santa Margherita di Pula (Cagliari)
Menardi, G., De Stefano, D.. (2015) Density-based clustering multiplex networks, Books of Abstracts of the International Federation of Classification Societies (IFCS). Bologna
Menardi, G., De Stefano, D.. (2014) Modal clustering of social network. Proceedings of the 47th SIS Scientific Meeting of the Italian Statistical Society. Cagliari, ISBN: 978-88-8467-874-4.
Menardi, G. (2013) Determining the number of clusters: a problem of definition or estimation? Book of Abstracts of the Conference of the International Federation of Classification Societies, IFCS2013. Tillburg.
Azzalini, A., Menardi, G. (2011) A Procedure for detecting high density connected regions in clustering methods. Proceedings of the 7th Conference on Statistical Computation and Complex Systems, Padova. ISBN: 978-88-6129-753-1.
Menardi, G., Torelli, N. (2009) Some issues in building and assessing classification rules with extremely skewed datasets. Proceedings of the 7th Meeting of the Classification and data Analysis Group of the Italian Statistical Society (Invited Papers), Catania, ISBN 978-88-6129-406-6, Cleup (Padova).
Menardi, G., (2009) Some issues emerging in evaluating the risk of default for SMEs. Proceedings of the Sixth Conference S.co (Invited Papers), Milano, ISBN 978-88-387-4385-1, Maggioli, (Rimini).
Menardi, G. (2008) Effects of Sample selection in credit scoring models, Atti della XLIV Riunione scientifica della Società Italiana di Statistica, Arcavacata di Rende (CS), ISBN 978-88-6129-228-4 Cleup, (Padova).
Menardi,G. Torelli, N. (2008) Evaluating enterprise risk of default using boosting procedures, Proceedings of the First Joint Meeting of the Société Francophoné de Classification and the Classification and Data Analysis Group of the Italian Statistical Society, Caserta, ISBN 978-88-495-1656-2, Edizioni Scientifiche italiane (Napoli).
Menardi, G., Torelli, N. (2007) Multimodal projection pursuit using the adjusted critical bandwidth. Book of Short Papers, Classification and Data Analysis Group of the Italian Statistical Society. Eum – Edizioni Università di Macerata. ISBN 978-88-6056-020-9.
Menardi, G. (2007) Evaluating clusters quality using a technique based on density estimation. Atti della Quinta Riunione Scientifica S.co. Disponibile su http://venus.unive.it/sco2007/ocs/ viewabstract.php?id=52.
Menardi, G. (2006) Variable Kernel density estimate: a new proposal. Atti della XLIII Riunione Scientifica della Società Italiana di Statistica. ISBN 88-7178-791-9,Cleup, Padova.
Menardi, G., Monte, A., Pauli, F. (2004) Unemployment estimation for Friuli- Venezia Giulia provinces by Times Series Small Area Models. Atti della XLII Riunione Scientifica della Società Italiana di Statistica. ISBN 88-7178-034-5, Cleup (Padova).
PhD Thesis
Menardi, G. (2006) Un metodo di raggruppamento basato sulla densità: alcuni approfondimenti. Tesi di dottorato in Statistica Applicata alle Scienze Economiche e Sociali, Dipartimento di Scienze statistiche, Università degli Studi di Padova.