Scientific Program and Schedule

September 2, 2020

15.30-15.45     Opening

15.45-16.40     Keynote Lecture 1
Thomas Brendan Murphy (University College Dublin, School of Mathematics & Statistics, Dublin, Ireland)
Model-Based Clustering with Parsimonious and Sparse Covariance
Chair: Maurizio Vichi (Italy)

16.45-18.15     Talk Session 1
Supervised and semisupervised clustering
Chair: Malgorzata Bogdan (Poland)

• Andrea Cappozzo ((University of Milano-Bicocca, Italy), Francesca Greselin, Thomas Brendan Murphy
  Variable selection for robust model-based classification of contaminated spectra
• Christian Hennig (University of Bologna, Italy), Davide Rapagnani
  k-means and Regression Prediction
• Luca Frigau (University of Cagliari, Italy), Giulia Contu and Francesco Mola
  Tree-based community detection clustering

September 4, 2020

15.30-16.25     Keynote Lecture 2
Kweku Abraham, Ismael Castillo, Elisabeth Gassiat (Laboratoire de Mathématiques d'Orsay, Université Paris-Saclay, France)
Bayesian multiple testing in Hidden Markov Models
Chair: Luis Angel García-Escudero (Spain)

16.30-18.00     Talk Session 2
Models for complex data structures
Chair: Francesca Greselin (Italy)

• Brunero Liseo (University of Rome La Sapienza, Italy), Andrea Tancredi
  Mixture modeling and deduplication problems
• Monia Ranalli (University of Rome La Sapienza, Italy), Roberto Rocci
  Mixture of factor analyzers for mixed-type data via a composite likelihood approach
• Salvatore D. Tomarchio (University of Catania, Italy), Antonio Punzo, Luca Bagnato
  Clustering three-way data with a new mixture of Gaussian scale mixtures

September 11, 2020

15.30-16.25     Keynote Lecture 3
Jiahua Chen (Department of Statistics, University of British Columbia, Vancouver, Canada)
Development of EM-tests in Finite Mixture Models
Chair: Weixin Yao (USA)

16.30-18.00     Talk Session 3
Hierarchical modeling in clustering
Chair: Roberto Rocci (Italy)

• Zsuzsa Bakk (Leiden University, The Netherlands), Roberto Di Mari, Jennifer Oser
  Two-stage multilevel latent class analysis with co-variates in the presence of direct effects
• Carlo Cavicchia, Maurizio Vichi (University of Rome La Sapienza, Italy), Giorgia Zaccaria
  A parsimonious parameterization of a nonnegative correlation matrix
• Sylvia Frühwirth-Schnatter, Jan Greve, Bettina Grün (Wirtschaftsuniversität Wien, Austria), Gertraud Malsiner-Walli
  Model-Based Clustering with Bayesian Gaussian Mixtures

September 18, 2020

15.30-16.25     Keynote Lecture 4
Gianluca Bontempi (Machine Learning Group - Département d'Informatique, Université Libre de Bruxelles, Belgium)
From supervised learning to causal inference in large dimensional settings
Chair: Kim De Roover (The Netherlands)

16.30-18.00     Talk Session 4
Model-based clustering with factor analyzers
Chair: Volodymyr Melnykov (USA)

• Kim De Roover (Tilburg School of Social and Behavioral Sciences, The Netherlands), Geoffrey McLachlan
  Measurement invariance from the inside out: Nested mixtures of factor analyzers for capturing non-invariance within groups
• Michael P.B. Gallaugher, Paul D. McNicholas (McMaster University, Canada)
  Clustering Three-Way Data via Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers
• Wangshu Tu (Binghamton University, USA), Yuan Fang, Sanjeena Subedi
  A novel biclustering algorithm for microbiome data

September 25, 2020

15.30-16.25     Keynote Lecture 5
Juan Antonio Cuesta-Albertos , Subhajit Dutta (Departamento de Matemáticas, Facultad de Ciencias, Universidad de Cantabria, Spain)
The blessing of (infinite) dimensionality
Chair: Angela Montanari (Italy)

16.30-18.00     Talk Session 5
Models for categorical data
Chair: Paul McNicholas (Canada)

• Filippo Antonazzo (Inria, Université de Lille, CNRS, France), Christophe Biernacki, Christine Keribin
  A binned technique for scalable model-based clustering on huge datasets
• Leonie V.D.E. Vogelsmeier (Tilburg University, The Netherlands), Jeroen K. Vermunt, Kim De Roover
  Latent Markov Factor Analysis: A mixture modeling approach for evaluating within- and between-person measurement model differences in intensive longitudinal data
• Yingying Zhang, Volodymyr Melnykov (University of Alabama, Tuscaloosa, AL, USA)
  Finite mixture modeling of time-dependent categorical sequencess

Papers to be presented in Video-Posters

• Marco Bee (University of Trento, Italy)
  Lognormal or Pareto? A classification approach


• Luca Coraggio (University of Naples Federico II, Italy), Pietro Coretto
  In-sample and cross-validated likelihood-type criteria for clustering selection


• F.J. Clouth (Tilburg University, Tilburg, The Netherlands), S. Pauws, J.K. Vermunt
  On the use of inverse propensity weighting in latent class analysis


• Cristina Davino, Domenico Vistocco (University of Naples Federico II, Italy)
  Clustering and Modeling Data. A Quantile Regression Approach


• Francesco Denti, Andrea Cappozzo(University of Milano-Bicocca, Italy), and Francesca Greselin
  Bayesian Nonparametric Functional Novelty Detector


• Roberto Di Mari, Roberto Rocci and Stefano Antonio Gattone (University G. d’Annunzio, Chieti-Pescara, Italy)
  Lasso-penalized clusterwise linear regression modeling with the soft-LARS algorithm


• Luca Frigau (University of Cagliari, Italy), Tahir Ekin and Claudio Conversano
  Cluster Validity by Random Forests


• Massimo Mucciardi (University of Messina, Italy), Giovanni Pirrotta and Andrea Briglia
  EM Clustering method and first language acquisition


• Mariangela Sciandra (University of Palermo, Italy), Alessandro Albano, Antonella Plaia, Irene Carola Spera
  Impact of the COVID-19 pandemic on music: a method for clustering sentiments


• Gabriele Soffritti (University of Bologna, Italy)
  Estimating variances and covariances of the ML estimator under linear cluster-weighted models


• Hung Tong, Cristina Tortora (San José State University, USA)
  Cluster analysis and outlier detection with missing data