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)
Variable selection for robust model-based classification of contaminated spectra
k-means and Regression Prediction
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)
Mixture modeling and deduplication problems
Mixture of factor analyzers for mixed-type data via a composite likelihood approach
Clustering three-way data with a new mixture of Gaussian scale mixtures
18.10-18.40 Poster Discussion Session 1
Chair: Laura Anderlucci (Italy)
In-sample and cross-validated likelihood-type criteria for clustering selection
On the use of inverse propensity weighting in latent class analysis
Cluster analysis and outlier detection with missing data
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)
Two-stage multilevel latent class analysis with co-variates in the presence of direct effects
A parsimonious parameterization of a nonnegative correlation matrix
Model-Based Clustering with Bayesian Gaussian Mixtures
18.10-18.45 Poster Discussion Session 2
Chair: Monia Ranalli (Italy)
Lognormal or Pareto? A classification approach
Bayesian Nonparametric Functional Novelty Detector
Lasso-penalized clusterwise linear regression modeling with the soft-LARS algorithm
Estimating variances and covariances of the ML estimator under linear cluster-weighted models
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)
Measurement invariance from the inside out: Nested mixtures of factor analyzers for capturing non-invariance within groups
Clustering Three-Way Data via Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers
A novel biclustering algorithm for microbiome data
18.10-18.45 Poster Discussion Session 3
Chair: Salvatore D. Tomarchio (Italy)
Clustering and Modeling Data. A Quantile Regression Approach
Cluster Validity by Random Forests
EM Clustering method and first language acquisition
Impact of the COVID-19 pandemic on music: a method for clustering sentiments
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)
A binned technique for scalable model-based clustering on huge datasets
Latent Markov Factor Analysis: A mixture modeling approach for evaluating within- and between-person measurement model differences in intensive longitudinal data
Finite mixture modeling of time-dependent categorical sequencess
18.00-18.10 Closing
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