KEYNOTE TALKS
| Keynote talk 2 | Friday 26.8.2022 | 15:00 - 16:00 | Room: R1 |
| New graphical displays for classification | |||
| Speaker: P. Rousseeuw Co-authors: J. Raymaekers | Chair: TBA | ||
| Keynote talk 1 | Saturday 27.8.2022 | 13:55 - 14:45 | Room: R1 |
| A most surprising but useful result in semi-supervised learning (virtual) | |||
| Speaker: G. McLachlan | Chair: TBA | ||
| Keynote talk 3 | Sunday 28.8.2022 | 11:35 - 12:30 | Room: R1 |
| Distributed estimation through parallel approximants | |||
| Speaker: P. Wolfe Co-authors: A. Chakravorty, W.S. Cleveland | Chair: TBA | ||
PARALLEL SESSIONS
| Parallel session B: SDS2022 | Friday 26.8.2022 | 16:30 - 18:10 |
| Session SO012 | Room: R1 |
| Recent advances in dimension reduction and related methods | Friday 26.8.2022 16:30 - 18:10 |
| Chair: Yuichi Mori | Organizer: Yuichi Mori, Hiroshi Yadohisa |
| SO0176: M. van de Velden, A. Iodice D Enza, A. Markos | |
| Biplots in dimension reduction and clustering | |
| SO0182: K. Tanioka, H. Yadohisa | |
| Asymmetric MDS with sparse regularization term | |
| SO0187: Y. Terada, M. Yamamoto | |
| Regularized functional subspace clustering | |
| SO0153: W. Zhou, L. Zhang, H. Wang | |
| Estimation and inference of A heteroskedasticity model with latent semiparametric factors for panel data analysis |
| Session SO015 | Room: R2 |
| Bayesian learning | Friday 26.8.2022 16:30 - 18:10 |
| Chair: Igor Pruenster | Organizer: Igor Pruenster |
| SO0181: F. Liang, Z. Liu | |
| Statistical guarantees for variational automatic relevance determination | |
| SO0175: C. Villa, S. Walker, A. Kume | |
| An application of square root transformation for optimal prior selection | |
| SO0185: A. Canale, M. Guindani, L. D Angelo | |
| Bayesian nonparametric analysis of calcium imaging data | |
| SO0177: T. Rigon, A. Zito, D. Dunson | |
| A conjugate prior for the Dirichlet process precision parameter |
| Parallel session C: SDS2022 | Saturday 27.8.2022 | 09:00 - 10:15 |
| Session SO008 | Room: R1 |
| Statistical learning for network data with applications | Saturday 27.8.2022 09:00 - 10:15 |
| Chair: Yousri Slaoui | Organizer: Yousri Slaoui |
| SO0172: A. Ounajim, Y. Slaoui, P.-Y. Louis, D. Frasca, P. Rigoard | |
| Mixture of longitudinal factor analysis for modelling heterogeneous longitudinal multivariate data | |
| SO0204: L. Grill, Y. Slaoui, D. Nortershauser, S. Le Masson | |
| Usage of Bayesian neural network in deep reinforcement learning | |
| SC0202: Y. Slaoui | |
| Extension of the stochastic block model to handle networks with weighted nodes with application to EEG data |
| Session SO031 | Room: R2 |
| Flexible models for the analysis and classification of heterogeneous data | Saturday 27.8.2022 09:00 - 10:15 |
| Chair: Geoffrey McLachlan | Organizer: Geoffrey McLachlan |
| SO0163: M. Berrettini, G. Galimberti, S. Ranciati | |
| Semiparametric finite mixture of regression models with Bayesian P-splines | |
| SO0191: D. Ahfock, G. McLachlan | |
| An EM algorithm for semi-supervised learning with data augmentation | |
| SO0192: H. Nguyen | |
| (SAM)$^2$: A family of sequential sample averaging algorithms via majorization--minimization |
| Parallel session D: SDS2022 | Saturday 27.8.2022 | 10:45 - 12:25 |
| Session SO010 | Room: R1 |
| Text based indicators in economics and finance | Saturday 27.8.2022 10:45 - 12:25 |
| Chair: Peter Winker | Organizer: Maria Brigida Ferraro, Peter Winker |
| SO0180: C. Funk, E. Toenjes, L. Breuer, R. Teuber | |
| Difference in SDG reporting of research articles using zero-shot text classification | |
| SO0196: I. Cozzolino, M.B. Ferraro, P. Winker | |
| A novel fuzzy spectral clustering approach for text data | |
| SO0156: S. Makarova, W. Charemza, K. Rybinski | |
| Anti-pandemic restrictions, uncertainty and sentiment in seven countries | |
| SO0171: P. Winker, D. Lenz, A. Latifi | |
| Text based innovation indicators a progress report |
| Session SO023 | Room: R2 |
| Contemporary computational and methodological challenges in environmental data | Saturday 27.8.2022 10:45 - 12:25 |
| Chair: Abhirup Datta | Organizer: Stefano Castruccio |
| SO0152: J. Park, I.H. Jin | |
| Bayesian model selection for ultrahigh dimensional doubly intractable distributions | |
| SO0160: W. Chang, J. Wang, S. Bhatnagar, S. Kim | |
| Computer model calibration with time series data using deep learning and quantile regression | |
| SO0162: B. Sanso, X. Zheng, T. Kottas | |
| Nearest neighbors processes for non-Gaussian geostatistical data | |
| SO0184: L. Ippoliti, A. Ferretti, R. Bhansali, P. Valentini | |
| Long memory random fields on regular lattices |
| Parallel session F: SDS2022 | Saturday 27.8.2022 | 14:55 - 16:35 |
| Session SO021 | Room: R1 |
| Analytical challenges with complex data analysis | Saturday 27.8.2022 14:55 - 16:35 |
| Chair: Anna Gottard | Organizer: Taps Maiti |
| SO0161: S. Chatterjee | |
| Bayesian inference in large complex networks | |
| SO0198: A. Montanari, L. Anderlucci | |
| Perturbing data to address dataset shift in supervised classification | |
| SO0205: X. Bi, X. Shen | |
| Distribution-invariant differential privacy | |
| SO0206: A. Gottard, A. Panzera | |
| Bayesian networks for dihedral angles |
| Session SO033 | Room: R2 |
| Nonasymptotic statistics and econometric | Saturday 27.8.2022 14:55 - 16:35 |
| Chair: Zhao Ren | Organizer: Zhao Ren |
| SO0168: Z. Ren | |
| Heteroskedastic sparse PCA in high dimensions | |
| SO0170: W. Wang | |
| $L^2$ inference of change-points for high-dimensional time series | |
| SO0173: R. Chen | |
| Kronecker product approximation for matrix approximation, denoising and completion | |
| SO0174: W. Zhou, K.M. Tan, X. He | |
| Robust estimation and inference for expected shortfall regression |
| Parallel session G: SDS2022 | Saturday 27.8.2022 | 17:05 - 18:45 |
| Session SO006 | Room: R1 |
| Functional and object data analysis | Saturday 27.8.2022 17:05 - 18:45 |
| Chair: TBA | Organizer: Jane-Ling Wang |
| SO0166: P. Dubey, H.-G. Mueller | |
| Modeling time-varying random objects and dynamic networks | |
| SO0167: S. Golovkine, V. Patilea, N. Klutchnikoff | |
| Learning the regularity of curves in functional data analysis and applications | |
| SO0164: C. Zhu, H.-G. Mueller | |
| Spherical autoregressive models, with application to distributional and compositional time series | |
| SO0159: X. Zhang, Z. Qi, R. Miao | |
| Proximal learning for individualized treatment regimes under unmeasured confounding |
| Session SO019 | Room: R2 |
| Machine learning for spatial analysis | Saturday 27.8.2022 17:05 - 18:45 |
| Chair: TBA | Organizer: Bertrand Clarke |
| SO0183: A. Datta | |
| Generalizing random forests for spatially correlated data | |
| SO0190: R. Guhaniyogi | |
| Data Compression and Distributed Inference in Spatial Analysis | |
| SO0208: A. Jaeger | |
| Classification of ENSO phases using topological data analysis | |
| SO0201: D. Hammerling, H. Huang, L. Blake, M. Katzfuss | |
| Nonstationary spatial modeling of massive global satellite data |
| Parallel session H: SDS2022 | Sunday 28.8.2022 | 09:00 - 11:05 |
| Session SC014 | Room: R1 |
| Statistical data science | Sunday 28.8.2022 09:00 - 11:05 |
| Chair: TBA | Organizer: CMStatistics |
| SC0178: M. Felix, D. La Vecchia | |
| Semiparametric estimation for time series: A frequency domain approach based on optimal transportation theory | |
| SC0179: L. Mancini | |
| Portfolio choice when stock returns may disappoint: An empirical analysis based on L-moments | |
| SC0193: F. Setoudehtazangi, M. Caporin | |
| Mixtures, heavy tails, asymmetry and conditional heteroskedasticity in financial returns | |
| SC0199: S. Jokubaitis, D. Celov | |
| Business cycle synchronization in the EU: A regional-sectoral look through soft clustering and wavelet decomposition | |
| SC0165: O. Davidov | |
| Graphical linear models for paired comparison data |
| Session SO004 | Room: R2 |
| Statistical data science (virtual) | Sunday 28.8.2022 09:00 - 11:05 |
| Chair: Maria Brigida Ferraro | Organizer: Maria Brigida Ferraro |
| SV0189: Z. Li | |
| Change point inference for high-dimensional correlation matrix | |
| SV0194: D. Chakrabarty, N. Paul | |
| Estimating specification parameters while learning unknowns, in a misspecified model | |
| SC0169: M. Zafer Merhi, D. Lin, A. Essaghir, Z. Shkedy | |
| Identification of antigen specificity in single cell RNAseq experiments using biclustering methods for binary data | |
| SV0188: S. Chen | |
| Machine learning based mass imputation approaches for combining probability sample and nonprobability sample | |
| SV0158: M.A. Kaygusuz, V. Purutcuoglu | |
| Effect of bootstrapping in sparse biological data and model selection via likelihood ratio test |