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Machine Learning, Optimization, and Data Science

7th International Conference, LOD 2021, Grasmere, UK, October 4–8, 2021, Revised Selected Papers, Part I

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Giuseppe Nicosia

    1. University of Catania, Catania, Italy

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  2. Varun Ojha

    1. Department of Computer Science, University of Reading, Reading, UK

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  3. Emanuele La Malfa

    1. Department of Computer Science, University of Oxford, Oxford, UK

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  4. Gabriele La Malfa

    1. Cambridge Judge Business School, University of Cambridge, Cambridge, UK

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  5. Giorgio Jansen

    1. Department of Biochemistry, University of Cambridge, Cambridge, UK

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  6. Panos M. Pardalos

    1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA

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  7. Giovanni Giuffrida

    1. University of Catania, Catania, Italy

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  8. Renato Umeton

    1. Department of Informatics, Dana-Farber Cancer Institute, Boston, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13163)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: LOD 2021.

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Table of contents (45 papers)

  1. Front Matter

    Pages i-xxiv
    Download chapter PDF

  2. Effect of Geometric Complexity on Intuitive Model Selection

    • Eugenio Piasini, Vijay Balasubramanian, Joshua I. Gold
    Pages 1-24

  3. Training Convolutional Neural Networks with Competitive Hebbian Learning Approaches

    • Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
    Pages 25-40

  4. Towards Understanding Neuroscience of Realisation of Information Need in Light of Relevance and Satisfaction Judgement

    • Sakrapee Paisalnan, Frank Pollick, Yashar Moshfeghi
    Pages 41-56

  5. New Optimization Approaches in Malware Traffic Analysis

    • Ivan Letteri, Antonio Di Cecco, Giuseppe Della Penna
    Pages 57-68

  6. Topological Properties of Mouse Neuronal Populations in Fluorescence Microscopy Images

    • Margarita Zaleshina, Alexander Zaleshin
    Pages 69-80

  7. Employing an Adjusted Stability Measure for Multi-criteria Model Fitting on Data Sets with Similar Features

    • Andrea Bommert, Jörg Rahnenführer, Michel Lang
    Pages 81-92

  8. A Study on Relevant Features for Intraday S&P 500 Prediction Using a Hybrid Feature Selection Approach

    • Mahinda Mailagaha Kumbure, Christoph Lohrmann, Pasi Luukka
    Pages 93-104

  9. ViT - Inception - GAN for Image Colourisation

    • Tejas Bana, Jatan Loya, Siddhant Kulkarni
    Pages 105-118

  10. On Principal Component Analysis of the Convex Combination of Two Data Matrices and Its Application to Acoustic Metamaterial Filters

    • Giorgio Gnecco, Andrea Bacigalupo
    Pages 119-123

  11. Mixing Consistent Deep Clustering

    • Daniel Lutscher, Ali el Hassouni, Maarten Stol, Mark Hoogendoorn
    Pages 124-137

  12. Utilizing Predictive Models to Identify the Influence of Full Prior Distribution in Hypothesis Testing Problems

    • Yuval Ben-David, Gail Gilboa-Freedman
    Pages 138-143

  13. Optimally Weighted Ensembles for Efficient Multi-objective Optimization

    • Gideon Hanse, Roy de Winter, Bas van Stein, Thomas Bäck
    Pages 144-156

  14. Anomaly Detection in Smart Grid Network Using FC-Based Blockchain Model and Linear SVM

    • Saurabh Shukla, Subhasis Thakur, John G. Breslin
    Pages 157-171

  15. Unsupervised PulseNet: Automated Pruning of Convolutional Neural Networks by K-Means Clustering

    • David Browne, Michael Giering, Steven Prestwich
    Pages 172-184

  16. A Noisy-Labels Approach to Detecting Uncompetitive Auctions

    • Natalya Goryunova, Artem Baklanov, Egor Ianovski
    Pages 185-200

  17. Deep Autonomous Agents Comparison for Self-driving Cars

    • Alessandro Riboni, Antonio Candelieri, Matteo Borrotti
    Pages 201-213

  18. Method for Generating Explainable Deep Learning Models in the Context of Air Traffic Management

    • Keith Rudd, Michelle Eshow, Mary Gibbs
    Pages 214-234

  19. ShufText: A Simple Black Box Approach to Evaluate the Fragility of Text Classification Models

    • Rutuja Taware, Shraddha Varat, Gaurav Salunke, Chaitanya Gawande, Geetanjali Kale, Rahul Khengare et al.
    Pages 235-249

  20. A Framework for Imbalanced Time-Series Forecasting

    • Luis P. Silvestrin, Leonardos Pantiskas, Mark Hoogendoorn
    Pages 250-264
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Other volumes

  1. Machine Learning, Optimization, and Data Science

  2. Machine Learning, Optimization, and Data Science

Keywords

About this book

This two-volume set, LNCS 13163-13164, constitutes the refereed proceedings of the 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021, together with  the first edition of the Symposium on Artificial Intelligence and Neuroscience, ACAIN 2021.

The total of 86 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 215 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.

Editors and Affiliations

  • University of Catania, Catania, Italy

    Giuseppe Nicosia, Giovanni Giuffrida

  • Department of Computer Science, University of Reading, Reading, UK

    Varun Ojha

  • Department of Computer Science, University of Oxford, Oxford, UK

    Emanuele La Malfa

  • Cambridge Judge Business School, University of Cambridge, Cambridge, UK

    Gabriele La Malfa

  • Department of Biochemistry, University of Cambridge, Cambridge, UK

    Giorgio Jansen

  • Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA

    Panos M. Pardalos

  • Department of Informatics, Dana-Farber Cancer Institute, Boston, USA

    Renato Umeton

Bibliographic Information

  • Book Title: Machine Learning, Optimization, and Data Science

  • Book Subtitle: 7th International Conference, LOD 2021, Grasmere, UK, October 4–8, 2021, Revised Selected Papers, Part I

  • Editors: Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Giorgio Jansen, Panos M. Pardalos, Giovanni Giuffrida, … Renato Umeton

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-95467-3

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2022

  • Softcover ISBN: 978-3-030-95466-6Published: 02 February 2022

  • eBook ISBN: 978-3-030-95467-3Published: 01 February 2022

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXIV, 644

  • Number of Illustrations: 15 b/w illustrations, 186 illustrations in colour

  • Topics: Computer Applications

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