Agenda

Day 2: July 6, 2023 (THU)

Start Time (ECT)	End Time (ECT)	Track	Session Title	Speaker(s)	Room	Chair
9:00	9:25	Invited Sessions - Psychometrics and Machine learning	Identifying the Onset of Careless Responding: A Machine Learning Approach	Andreas Alfons	C.003	Andreas Alfons
9:25	9:50	Invited Sessions - Psychometrics and Machine learning	Quantifying effects of rating-scale response bias: robustness properties of correlation measures	Archimbaud Aurore	C.003	Andreas Alfons
9:50	10:15	Invited Sessions - Psychometrics and Machine learning	Exploring the measurement model in (high-dimensional) multigroup data: Regularized joint latent variable analysis	Katrijn Van Deun	C.003	Andreas Alfons
10:15	10:40	Invited Sessions - Psychometrics and Machine learning	Using machine learning for study planning in psychology	Rudolf Debelak	C.003	Andreas Alfons
9:00	9:25	Invited Sessions - Probabilistic predictions and forecasting	Reliable uncertainty estimation via proper scores	Florian Buettner	C.002	Viktor Bengs
9:25	9:50	Invited Sessions - Probabilistic predictions and forecasting	Using High-Frequency data to Improve Forecast Evaluation	Hajo Holzmann	C.002	Viktor Bengs
9:50	10:15	Invited Sessions - Probabilistic predictions and forecasting	A Gentle Introduction to Conformal Regressors and Predictive Systems	Henrik Boström	C.002	Viktor Bengs
10:15	10:40	Invited Sessions - Probabilistic predictions and forecasting	An introduction to Venn-ABERS Predictors	Paolo Toccaceli	C.002	Viktor Bengs
10:40	11:10	Coffee-Break	Coffee-Break	-	Hall	-
11:10	11:30	Contributed Sessions -Bayesian statistics	Bayesian Geographically Weighted Regression with Fused Lasso Penalty	Toshiki Sakai	C.101	Winfried Steiner
11:30	11:50	Contributed Sessions -Bayesian statistics	Objective Bayesian inference for recall-based studies with application to breastfeeding data	Vikas Barnwal	C.101	Winfried Steiner
11:50	12:10	Contributed Sessions -Bayesian statistics	Bayesian Systemic Risk Analysis using Latent Space Network Models	Mike K.P. So	C.101	Winfried Steiner
11:10	11:30	Contributed Sessions -Machine and deep learning applications	Investigating the Impact of Word Embeddings on Fake News Detection	Adalbert F.X. Wilhelm	C.103	Lynn D'eer
11:30	11:50	Contributed Sessions -Machine and deep learning applications	Evaluating the Risk Alignment of Preference-Based Reinforcement Learning Agents	Marvin Schweizer	C.103	Lynn D'eer
11:50	12:10	Contributed Sessions -Machine and deep learning applications	Graph Neural Networks for Food Recommendation Systems	Leonid Kholkine	C.103	Lynn D'eer
12:10	12:30	Contributed Sessions -Machine and deep learning applications	The impact of shocks on the company’s market valuation – An empirical analysis during the Covid-19 pandemic	Kai Fischer	C.103	Lynn D'eer
11:10	11:30	Contributed Sessions -Clustering	Quantifying variable importance in cluster analysis	Christian Hennig	C.002	Stefan Van Aelst
11:30	11:50	Contributed Sessions -Clustering	Hierarchical variable clustering using singular value decomposition	Jan Bauer	C.002	Stefan Van Aelst
11:50	12:10	Contributed Sessions -Clustering	Watson: An R Package for Fitting Mixtures of Watson Distributions	Lukas Sablica	C.002	Stefan Van Aelst
12:10	12:30	Contributed Sessions -Clustering	Robust co-clustering for data exploration and anomaly detection in the high-dimensional setting	Edoardo Fibbi	C.002	Stefan Van Aelst
11:10	11:30	Contributed Sessions -Statistical methodology	Compositional splines for representation of bivariate density functions	Stanislav Škorňa	C.102	Peter Filzmoser
11:30	11:50	Contributed Sessions -Statistical methodology	Nonparametric Snake Test For Multivariate Skewness	Malgorzata Markowska	C.102	Peter Filzmoser
11:50	12:10	Contributed Sessions -Statistical methodology	On the Principle of Reflection in Genetic and Evolutionary Algorithms	Andreas Geyer-Schulz	C.102	Peter Filzmoser
12:10	12:30	Contributed Sessions -Statistical methodology	Evaluating Weights for Sample Selection Bias Correction	An-Chiao Liu	C.102	Peter Filzmoser
12:30	14:00	Lunch	Lunch	-	-	-
12:30	13:30	Members meeting GfKl	Members meeting GfKl	-	C.001	-
14:00	14:30	JDSSV	The Cellwise Minimum Covariance Determinant Estimator	Peter Rousseeuw	C.003	Patrick Groenen and Stefan Van Aelst
14:30	15:00	JDSSV	Aspects of Trustworthy Reinforcement Learning	Ann Nowé	C.003	Patrick Groenen and Stefan Van Aelst
15:00	15:30	JDSSV	Information about JDSSV - Call for Review Editors for the Journal of Data Science, Statistics and Visualization	Patrick Groenen and Stefan Van Aelst	C.003	Patrick Groenen and Stefan Van Aelst
15:30	16:00	Coffee-Break	Coffee-Break	-	Hall	-
16:00	17:00	Keynote Day 2	An educational tour on quantile regression	Domenico Vistocco	C.003	Mia Hubert
18:00	20:00	Reception @ City Hall	Reception @ City Hall	-	City Hall	-