Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Session Overview |
| Date: Wednesday, 13/Mar/2024 | ||||
| 9:10am - 9:30am |
Opening Location: Collegezaal A Chair: Ansgar Steland Chair: Geurt Jongbloed |
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| 9:30am - 10:30am |
Plenary Talk: Wei-Biao Wu Location: Collegezaal A Chair: Ansgar Steland Concentration bounds for statistical learning for time dependent data |
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| 10:30am - 11:10am |
Coffee break |
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| 11:10am - 12:25pm |
Multivariate Analysis and Copulas Location: Commissiekamer 3 Chair: Eckhard Liebscher High-dimensional copula-based dependence 11:35am - 12:00pm Vine copulas for stochastic volatility 12:00pm - 12:25pm Sparse M-estimators in semi-parametric copula models |
Time Series Analysis Location: Collegezaal A Chair: Ansgar Steland Change-Point Synchronization Testing in Multiple Time-Series 11:35am - 12:00pm Multiple change point detection in functional data with applications to biomechanical fatigue data 12:00pm - 12:25pm Bootstrap convergence rates for the maximum of an increasing number of autocovariances and autocorrelations under strict stationarity |
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| 12:25pm - 1:30pm |
Lunch |
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| 1:30pm - 3:10pm |
High-dimensional Statistics Location: Collegezaal C Chair: Nestor Parolya Signpost testing to navigate the high-dimensional parameter space of the linear regression model 1:55pm - 2:20pm High-dimensional vine copula regression for mixed continuous-ordinal features 2:20pm - 3:10pm Reviving pseudo-inverses: Asymptotic properties of large dimensional Moore-Penrose and Ridge-type inverses with applications |
Shape-constrained inference Location: Commissiekamer 3 Chair: Geurt Jongbloed Isotonic Distributional Regression - Likelihood Ratio Order and Total Positivity 1:55pm - 2:20pm Single-index mixture cure model under monotonicity constraints 2:20pm - 2:45pm Convex loss selection via score matching 2:45pm - 3:10pm A comparison between Dirichlet process-based inference and shape-constrained inference for the Wicksell's inverse problem. |
Time Series Analysis Location: Collegezaal A Chair: Ansgar Steland Detection of breaks in weak location time series models with quasi-Fisher scores 2:20pm - 2:45pm Online Detection of Changes in Moment-Based Projections: When to Retrain Deep Learners or Update Portfolios? 2:45pm - 3:10pm Semi-continuous time series for sparse data with volatility clustering |
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| 3:10pm - 3:40pm |
Coffee break |
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| 3:40pm - 5:45pm |
Econometrics Location: Collegezaal B Chair: Julia Schaumburg Interactive Effects of Temperature and Precipitation on Global Economic Growth 4:05pm - 4:30pm Recovering latent linkage structures and spillover effects with structural breaks in panel data models 4:30pm - 4:55pm Joint Modeling and Estimation of Global and Local Cross-Sectional Dependence in Panel Data Sets 4:55pm - 5:20pm Age-specific transmission dynamics of SARS-CoV-2 during the first two years of the pandemic 5:20pm - 5:45pm Plausible GMM via Avenue Bayes |
Machine Learning and Inference in Advanced Applications Location: Collegezaal A Chair: Ansgar Steland Chair: Ewaryst Rafajlowicz The use of neural networks and PCA dimensionality reduction in filling missing fragments in high-dimensional time series 4:05pm - 4:30pm Test bench automation with Safe Active Learning using Gaussian Processes 4:30pm - 4:55pm Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Price Forecasting 4:55pm - 5:20pm Semi-Structured Regression 5:20pm - 5:45pm Forecasting the electricity demand flexibility via data-driven inverse optimization |
Statistics for Stochastic Processes Location: Collegezaal C Chair: Fabian Mies Spectral calibration of time-inhomogeneous exponential Lévy models 4:05pm - 4:30pm Kolmogorov-Smirnov Distribution and Self-Similarity of fractional Brownian motion 4:30pm - 4:55pm Asymptotic Efficiency for Fractional Brownian Motion 4:55pm - 5:20pm Bridge simulation for manifold-valued semimartingales 5:20pm - 5:45pm Constructing Confidence Intervals for Compound Poisson Process |
Spatial Statistics Location: Commissiekamer 3 Chair: Philipp Otto Multivariate functional additive mixed models 4:05pm - 4:30pm Multivariate Functional Spatial Data: A Principal Component Analysis Approach 4:30pm - 4:55pm Spatial Dependencies in Stock Returns 4:55pm - 5:20pm New STINARMA class of models in the analysis of space-time series of counts 5:20pm - 5:45pm A non-stationary spatio-temporal precipitation model for Austria |
| 6:00pm - 7:30pm |
Assembly of AG-ZQS members Location: Commissiekamer 3 |
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| 7:30pm - 10:00pm |
Welcome Reception We welcome all participants of the workshop for some food and drinks at Delft X Cafe. |
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| Date: Thursday, 14/Mar/2024 | |||
| 9:00am - 10:00am |
Plenary Talk: Ingrid Van Keilegom Location: Collegezaal B Chair: Fabian Mies Tests of exogeneity in proportional hazards models with censored data |
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| 10:00am - 10:30am |
Coffee break |
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| 10:30am - 12:10pm |
Discrete Time Series Location: Commissiekamer 3 Chair: Christian Weiß A general framework for compound-Poisson INAR and INGARCH models 10:55am - 11:20am Predictive inference for count data time series 11:20am - 11:45am Joint vector-autoregressive modeling of real- and integer-valued time series with full autoregressive parameter range 11:45am - 12:10pm Absolute regularity of non-stationary count time series |
Statistical Process Monitoring Location: Collegezaal C Chair: Sven Knoth Covariate-adjusted Sensor Outputs for Structural Health Monitoring: A Functional Data Approach 10:55am - 11:20am A Technical Note on Self-starting Regression Control Charts 11:20am - 11:45am Predictive Ratio Cusum (PRC): A Bayesian Approach in Online Change Point Detection of Short Runs 11:45am - 12:10pm AI and the Future of Work in Analytics: insights from a first attempt to Augment ChatGPT and to assess the Quality of Generative AI Analytics capabilities |
Statistical Learning Location: Collegezaal B Chair: Johannes Lederer Modern Extremes: Methods, Theories, and Algorithms 10:55am - 11:20am Image classification: A new statistical viewpoint 11:20am - 11:45am Dropout Regularization Versus \ell_2-Penalization in the Linear Model 11:45am - 12:10pm Inference on derivatives of high dimensional regression function with deep neural network(NN) |
| 12:10pm - 1:10pm |
Lunch |
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| 1:10pm - 2:50pm |
Bayesian Nonparametrics Location: Collegezaal B Chair: Aad van der Vaart Likelihood-based methods for low frequency diffusion data 2:00pm - 2:25pm Statistical guarantees for stochastic Metropolis-Hastings 2:25pm - 2:50pm The Bernstein-von Mises theorem for semiparametric mixtures |
High-dimensional Statistics Location: Collegezaal C Chair: Nestor Parolya Weak dependence and optimal quantitative self-normalized central limit theorems 1:35pm - 2:00pm Recent advances in large sample correlation matrices and their applications 2:00pm - 2:25pm Linear shrinkage for optimization in high dimensions 2:25pm - 2:50pm A test on the location of tangency portfolio for small sample size and singular covariance matrix |
Machine Learning and Inference in Advanced Applications Location: Commissiekamer 3 Chair: Ansgar Steland Chair: Ewaryst Rafajlowicz Joint empirical risk minimization for instance-dependent positive-unlabeled data 1:10pm - 1:40pm Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned by gradient descent Bayes Risk Consistency of Nonparametric Classification Rules for Spike Trains Data |
| 2:50pm - 3:20pm |
Coffee break |
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| 3:20pm - 4:20pm |
Plenary Talk: Fabrizio Ruggeri Location: Collegezaal B Chair: Nestor Parolya Advances in Adversarial Risk Analysis |
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| 4:30pm - 6:10pm |
Discrete Time Series Location: Collegezaal C Chair: Christian Weiß Modeling multivariate ordinal time series 4:55pm - 5:20pm Using Spatial Ordinal Patterns for Non-parametric Testing of Spatial Dependence 5:20pm - 5:45pm Multivariate Motion Patterns and Applications to Rainfall Radar Data 5:45pm - 6:10pm Depth patterns |
Multivariate Analysis and Copulas Location: Commissiekamer 3 Chair: Eckhard Liebscher Hierarchical variable clustering based on the predictive strength between random vectors 4:55pm - 5:20pm Kendall’s tau estimator for zero-inflated count data 5:20pm - 5:45pm Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions |
Statistical Learning Location: Collegezaal B Chair: Johannes Lederer Inference via robust optimal transportation: theory and methods 4:55pm - 5:20pm Inference for topological data analysis 5:20pm - 5:45pm Multi-study learning approaches |
| 7:00pm - 10:00pm |
Conference Dinner The dinner takes place at De Centrale, in the historical center of Delft. |
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| Date: Friday, 15/Mar/2024 | |||
| 9:00am - 10:15am |
Biostatistics and Reliability Location: Dance Studio A (Delft X) Chair: Fabian Mies Testing for sufficient follow-up in survival data with immunes 9:25am - 9:50am Combining profile likelihood with Bayesian estimation for Crow-AMSAA process 9:50am - 10:15am Optimizing the allocation of trials to sub-regions in multi-environment crop variety testing for the case of correlated genotype effects |
Multivariate Analysis and Copulas Location: Dance Studio B (Delft X) Chair: Eckhard Liebscher Multivariate dependence based on diagonal sections with an application to welfare analysis 9:25am - 9:50am Revisiting the Williamson transform in the context of multivariate Archimedean copulas 9:50am - 10:15am Approximation of copulas using Cramér-von Mises statistic: regularization and model selection |
Statistical Learning Location: Theatre Hall (Delft X) Chair: Johannes Lederer A Wasserstein perspective of Vanilla GANs 9:25am - 9:50am Asymptotic Theory for Constant Step Size Stochastic Gradient Descent 9:50am - 10:15am A Continuous-time Stochastic Gradient Descent Method for Continuous Data |
| 10:15am - 10:40am |
Coffee break |
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| 10:40am - 12:20pm |
Computational Statistics Location: Dance Studio B (Delft X) Chair: Ostap Okhrin A Platform-Agnostic Deep Reinforcement Learning Framework for Effective Sim2Real Transfer in Autonomous Driving 11:05am - 11:30am Adaptive factor modeling 11:30am - 11:55am Fitting bivariate copula mixture models 11:55am - 12:20pm Instabilities in Time Dependent Functional Profiles: Theory and Computation |
Statistics for Stochastic Processes Location: Theatre Hall (Delft X) Chair: Fabian Mies Smoothing for a SIR process 11:05am - 11:30am Nonparametric estimation of the interaction function in particle system models 11:30am - 11:55am Statistical analysis of a stochastic boundary model for high-frequency data from a limit order book 11:55am - 12:20pm Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations |
Time Series Analysis Location: Dance Studio A (Delft X) Chair: Ansgar Steland Statistical inference for intrinsic wavelet estimators of covariance matrices in a log-Euclidean manifold 11:05am - 11:30am Time-Varying Covariance Matrices Estimation by Nonlinear Wavelet Thresholding in a Log-Euclidean Riemannian Manifold 11:30am - 11:55am Using High-Frequency Data to Improve Forecast Evaluation 11:55am - 12:20pm On the weak convergence of the function-indexed sequential empirical process for nonstationary time series |
| 12:20pm - 1:00pm |
Short Lunch |
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| 1:00pm - 2:00pm |
Plenary Talk: Johannes Schmidt-Hieber Location: Theatre Hall (Delft X) Chair: Aad van der Vaart Towards a statistical foundation for machine learning methods |
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