Machine Learning, Optimization, and Data Science

1. Front Matter

   Pages i-xxiv

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2. Detection of Morality in Tweets Based on the Moral Foundation Theory

   • Luana Bulla, Stefano De Giorgis, Aldo Gangemi, Ludovica Marinucci, Misael Mongiovì

   Pages 1-13

3. Matrix Completion for the Prediction of Yearly Country and Industry-Level CO\(_2\) Emissions

   • Francesco Biancalani, Giorgio Gnecco, Rodolfo Metulini, Massimo Riccaboni

   Pages 14-19

4. A Benchmark for Real-Time Anomaly Detection Algorithms Applied in Industry 4.0

   • Philip Stahmann, Bodo Rieger

   Pages 20-34

5. A Matrix Factorization-Based Drug-Virus Link Prediction Method for SARS-CoV-2 Drug Prioritization

   • Yutong Li, Xiaorui Xu, Sophia Tsoka

   Pages 35-47

6. Hyperbolic Graph Codebooks

   • Pascal Mettes

   Pages 48-61

7. A Kernel-Based Multilayer Perceptron Framework to Identify Pathways Related to Cancer Stages

   • Marzieh Soleimanpoor, Milad Mokhtaridoost, Mehmet Gönen

   Pages 62-77

8. Loss Function with Memory for Trustworthiness Threshold Learning: Case of Face and Facial Expression Recognition

   • Stanislav Selitskiy, Natalya Selitskaya

   Pages 78-92

9. Machine Learning Approaches for Predicting Crystal Systems: A Brief Review and a Case Study

   • Gaetano Settembre, Nicola Corriero, Nicoletta Del Buono, Flavia Esposito, Rosanna Rizzi

   Pages 93-107

10. LS-PON: A Prediction-Based Local Search for Neural Architecture Search

    • Meyssa Zouambi, Julie Jacques, Clarisse Dhaenens

    Pages 108-122

11. Local Optimisation of Nyström Samples Through Stochastic Gradient Descent

    • Matthew Hutchings, Bertrand Gauthier

    Pages 123-140Open Access

12. Explainable Machine Learning for Drug Shortage Prediction in a Pandemic Setting

    • Jiye Li, Bruno Kinder Almentero, Camille Besse

    Pages 141-155

13. Intelligent Robotic Process Automation for Supplier Document Management on E-Procurement Platforms

    • Angelo Impedovo, Emanuele Pio Barracchia, Giuseppe Rizzo

    Pages 156-166

14. Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling

    • Kelly Smalenberger, Michael Smalenberger

    Pages 167-180

15. Sensitivity Analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial Chaos Expansion

    • Lukáš Novák, David Lehký, Drahomír Novák

    Pages 181-196

16. Transformers for COVID-19 Misinformation Detection on Twitter: A South African Case Study

    • Irene Francesca Strydom, Jacomine Grobler

    Pages 197-210

17. MI2AMI: Missing Data Imputation Using Mixed Deep Gaussian Mixture Models

    • Robin Fuchs, Denys Pommeret, Samuel Stocksieker

    Pages 211-222

18. On the Utility and Protection of Optimization with Differential Privacy and Classic Regularization Techniques

    • Eugenio Lomurno, Matteo Matteucci

    Pages 223-238

19. MicroRacer: A Didactic Environment for Deep Reinforcement Learning

    • Andrea Asperti, Marco Del Brutto

    Pages 239-252

20. A Practical Approach for Vehicle Speed Estimation in Smart Cities

    • Silvio Barra, Salvatore Carta, Antonello Meloni, Alessandro Sebastian Podda, Diego Reforgiato Recupero

    Pages 253-267

This two-volume set, LNCS 13810 and 13811,  constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022.
The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.

• adaptive control systems
• anomaly detection
• artificial intelligence
• automation
• bayesian networks
• big data
• computer crime
• computer security
• damage detection
• data mining
• database systems
• deep learning
• engineering structures
• evolutionary algorithms
• facial expression recognition
• fuzzy control
• fuzzy sets
• image processing
• machine learning

• University of Catania, Catania, Italy

  Giuseppe Nicosia, Giovanni Giuffrida

• University of Reading, Reading, UK

  Varun Ojha

• University of Oxford, Oxford, UK

  Emanuele La Malfa

• University of Cambridge, Cambridge, UK

  Gabriele La Malfa

• University of Florida, Gainesville, USA

  Panos Pardalos

• Free University of Bozen-Bolzano, Bolzano, Italy

  Giuseppe Di Fatta

• Dana-Farber Cancer Institute, Boston, USA

  Renato Umeton

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