Artificial Neural Networks and Machine Learning – ICANN 2022: 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part I
Author:   Elias Pimenidis ,  Plamen Angelov ,  Chrisina Jayne ,  Antonios Papaleonidas
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2022
Volume:   13529
ISBN:  

9783031159183


Pages:   761
Publication Date:   07 September 2022
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Artificial Neural Networks and Machine Learning – ICANN 2022: 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part I


Overview

The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022. The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications. Chapter “Sim-to-Real Neural Learning with Domain Randomisation for Humanoid Robot Grasping ” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Full Product Details

Author:   Elias Pimenidis ,  Plamen Angelov ,  Chrisina Jayne ,  Antonios Papaleonidas
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2022
Volume:   13529
Weight:   1.187kg
ISBN:  

9783031159183


ISBN 10:   3031159187
Pages:   761
Publication Date:   07 September 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Deep Learning.- , Neural Network Theory.- Relational Learning, Reinforcement Learning.- Natural language processing, Generative Models.- Graphical Models, Recommender Systems.- Image Processing, Recurrent Networks.- Evolutionary Neural Networks.- Unsupervised Neural Networks.- Neural Network Models.

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