Dynamic clustering of interval data using a Wasserstein-based distance A Irpino, R Verde Pattern Recognition Letters 29 (11), 1648-1658, 2008 | 152 | 2008 |
A new Wasserstein based distance for the hierarchical clustering of histogram symbolic data A Irpino, R Verde Data science and classification, 185-192, 2006 | 134 | 2006 |
New clustering methods for interval data M Chavent, FAT de Carvalho, Y Lechevallier, R Verde Computational statistics 21, 211-229, 2006 | 118 | 2006 |
Dynamic clustering of histogram data: using the right metric R Verde, A Irpino Selected contributions in data analysis and classification, 123-134, 2007 | 77 | 2007 |
Dynamic clustering of histogram data based on adaptive squared Wasserstein distances A Irpino, R Verde, FAT De Carvalho Expert Systems with Applications 41 (7), 3351-3366, 2014 | 65 | 2014 |
Acute thrombosis of prosthetic valves: a multivariate analysis of the risk factors for a life threatening A Renzulli, L De Luca, A Caruso, R Verde, D Galzerano, M Cotrufo Eur J Cardiothorac Surg 6, 412-20, 1992 | 64 | 1992 |
Basic statistics for distributional symbolic variables: a new metric-based approach A Irpino, R Verde Advances in Data Analysis and Classification 9, 143-175, 2015 | 54 | 2015 |
Comparing histogram data using a Mahalanobis–Wasserstein distance R Verde, A Irpino COMPSTAT 2008: Proceedings in Computational Statistics, 77-89, 2008 | 54 | 2008 |
Dynamic clustering of histograms using Wasserstein metric A Irpino, R Verde, Y Lechevallier COMPSTAT, 869-876, 2006 | 54 | 2006 |
Trois nouvelles méthodes de classification automatique de données symboliques de type intervalle M Chavent, F De Carvalho, Y Lechevallier, R Verde Revue de statistique appliquée 51 (4), 5-29, 2003 | 53 | 2003 |
A dynamical clustering algorithm for symbolic data R Verde, Y Lechevallier, F DE CARVALHO | 42 | 2001 |
Ordinary least squares for histogram data based on Wasserstein distance R Verde, A Irpino Proceedings of COMPSTAT'2010: 19th International Conference on Computational …, 2010 | 39 | 2010 |
Linear regression for numeric symbolic variables: a least squares approach based on Wasserstein Distance A Irpino, R Verde Advances in Data Analysis and Classification 9 (1), 81-106, 2015 | 38 | 2015 |
Principal component analysis of symbolic data described by intervals NC Lauro, R Verde, A Irpino Symbolic Data Analysis and the SODAS Software, ed. E. Diday and M. Noirhomme …, 2008 | 37 | 2008 |
A dynamical clustering algorithm for multi-nominal data R Verde, F de AT de Carvalho, Y Lechevallier Data analysis, classification, and related methods, 387-393, 2000 | 36 | 2000 |
Dimension reduction techniques for distributional symbolic data R Verde, A Irpino, A Balzanella IEEE transactions on cybernetics 46 (2), 344-355, 2015 | 34 | 2015 |
Factorial discriminant analysis on symbolic objects NC Lauro, R Verde, F Palumbo Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical …, 2000 | 32 | 2000 |
Clustering spatio-functional data: a model based approach E Romano, A Balzanella, R Verde Classification as a Tool for Research: Proceedings of the 11th IFCS Biennial …, 2010 | 30 | 2010 |
A multidimensional approach to conjoint analysis CN Lauro, G Giordano, R Verde Applied stochastic models and data analysis 14 (4), 265-274, 1998 | 30 | 1998 |
Spatial variability clustering for spatially dependent functional data E Romano, A Balzanella, R Verde Statistics and Computing 27, 645-658, 2017 | 24 | 2017 |