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Artificial Intelligence and Machine Learning: 34th Joint Benelux Conference, BNAIC/Benelearn 2022, Mechelen, Belgium, November 7–9, 2022, Revised Selected Papers de Toon Calders

Artificial Intelligence and Machine Learning: 34th Joint Benelux Conference, BNAIC/Benelearn 2022, Mechelen, Belgium, November 7–9, 2022, Revised Selected Papers: Communications in Computer and Information Science, cartea 1805

Editat de Toon Calders, Celine Vens, Jefrey Lijffijt, Bart Goethals
en Limba Engleză Paperback – 4 aug 2023
This book contains a selection of the best papers of the 34th Benelux Conference on Artificial Intelligence, BNAIC/ BENELEARN 2022, held in Mechelen, Belgium, in November 2022.
The 11 papers presented in this volume were carefully reviewed and selected from 134 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.
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Specificații

ISBN-13: 9783031391439
ISBN-10: 3031391438
Pagini: 179
Ilustrații: XII, 179 p. 48 illus., 43 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.28 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

Explainable Misinformation Detection from Text: A Critical Look.- Explaining Two Strange Learning Curves.- Recipe for Fast Large-scale SVM Training: Polishing, Parallelism, and more RAM!.- Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming.- A view on model misspecification in uncertainty quantification.- A Comparative Study of Sentence Embeddings for Unsupervised Extractive Multi-Document Summarization.- On-Device Deep Learning Location Category Inference Model.- Specificity and context dependent preferences in argumentation systems.- Model-Based Reinforcement Learning with State Abstraction: A Survey.- Symmetry and Dominance Breaking for Pseudo-Boolean Optimization.- Examining speaker and keyword uniqueness: Partitioning keyword spotting datasets for federated learning with the largest differencing method.