Artificial Intelligence, Big Data and Data Science in Statistics

- Part I Methodologies and Theoretical Studies. - One-Round Cross-Validation and Uncertainty Determination for Randomized Neural Networks with Applications to Mobile Sensors. - Scale Invariant and Robust Pattern Identification in Univariate Time Series, with Application to Growth Trend Detection in Music Streaming Data. - Fine-Tuned Parallel Piecewise Sequential Confidence Interval and Point Estimation Strategies for the Mean of a Normal Population: Big Data Context. - Statistical Learning for Change Point and Anomaly Detection in Graphs. - On the Robustness of Kernel-Based Pairwise Learning. - Global Sensitivity Analysis for the Interpretation of Machine Learning Algorithms. - Improving Gaussian Process Emulators with Boundary Information. - Part II Challenges and Solutions in Applications. - An Overview and General Framework for Spatiotemporal Modeling and Applications in Transportation and Public Health. - Introduction to Wafer Tomography: Likelihood-Based Prediction of Integrated-Circuit Yield. - Uncertainty Quantification Based on Bayesian Neural Networks for Predictive Quality. - Two Statistical Degradation Models of Batteries Under Different Operating Conditions. - Detecting Diamond Breakouts of Diamond Impregnated Tools for Core Drilling of Concrete by Force Measurements. - Visualising Complex Data Within a Data Science Loop: A Spatio-Temporal Example from Football. - Application of the Singular Spectrum Analysis on Electro luminescence Images of Thin-Film Photovoltaic Modules. - The Impact of the Lockdown Restrictions on Air Quality During COVID-19 Pandemic in Lombardy, Italy.