Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Rosa Meo, Fabrizio Silvestri

ISBN 10: 3031746260 / ISBN 13: 9783031746260

Published by Springer, 2025

About this Item

: Este libro recopila los trabajos presentados en los talleres internacionales de ECML PKDD 2023, celebrados en Turín, Italia, del 18 al 22 de septiembre de 2023. Los documentos presentados han sido cuidadosamente revisados y seleccionados entre más de 500 propuestas. El libro se organiza en cinco partes que cubren los avances en el aprendizaje automático interpretable, la inteligencia artificial, el descubrimiento responsable del conocimiento en la educación, la ciencia de datos para el bien social, el aprendizaje híbrido humano-máquina y las aplicaciones de aprendizaje automático para la salud y la industria farmacéutica. Este libro es una valiosa fuente de información para investigadores y profesionales interesados en las últimas tendencias y avances en el campo del aprendizaje automático y la minería de datos. EAN: 9783031746260 Tipo: Libros Categoría: Tecnología Título: Machine Learning and Principles and Practice of Knowledge Discovery in Databases Autor: Rosa Meo| Fabrizio Silvestri Editorial: Springer Idioma: en Páginas: 564 Formato: tapa blanda.

Seller Inventory # Happ-2025-10-22-371de6b8

Bibliographic Details

• Title: Machine Learning and Principles and Practice of Knowledge Discovery in Databases
• Publisher: Springer
• Publication Date: 2025
• Language: English
• ISBN 10: 3031746260
• ISBN 13: 9783031746260
• Binding: Soft cover
• Condition: Bueno

About this title

Synopsis

The five-volume set CCIS 2133-2137 constitutes the refereed proceedings of the workshops held in conjunction with the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, during September 18-22, 2023.

The 200 full papers presented in these proceedings were carefully reviewed and selected from 515 submissions. The papers have been organized in the following tracks:

Part I: Advances in Interpretable Machine Learning and Artificial Intelligence -- Joint Workshop and Tutorial; BIAS 2023 - 3rd Workshop on Bias and Fairness in AI; Biased Data in Conversational Agents; Explainable Artificial Intelligence: From Static to Dynamic; ML, Law and Society; 

Part II: RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education; SoGood 2023 – 8th Workshop on Data Science for Social Good; Towards Hybrid Human-Machine Learning and Decision Making (HLDM); Uncertainty meets explainability in machine learning; Workshop: Deep Learning and Multimedia Forensics. Combating fake media and misinformation; 

Part III: XAI-TS: Explainable AI for Time Series: Advances and Applications; XKDD 2023: 5th International Workshop on eXplainable Knowledge Discovery in Data Mining; Deep Learning for Sustainable Precision Agriculture; Knowledge Guided Machine Learning; MACLEAN: MAChine Learning for EArth ObservatioN; MLG: Mining and Learning with Graphs; Neuro Explicit AI and Expert Informed ML for Engineering and Physical Sciences; New Frontiers in Mining Complex Patterns; 

Part IV: PharML, Machine Learning for Pharma and Healthcare Applications; Simplification, Compression, Efficiency and Frugality for Artificial intelligence; Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making; 6th Workshop on AI in Aging, Rehabilitation and Intelligent Assisted Living (ARIAL); Adapting to Change: Reliable Multimodal Learning Across Domains; AI4M: AI for Manufacturing; 

Part V: Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications; Deep learning meets Neuromorphic Hardware; Discovery challenge; ITEM: IoT, Edge, and Mobile for Embedded Machine Learning; LIMBO - LearnIng and Mining for BlOckchains; Machine Learning for Cybersecurity (MLCS 2023); MIDAS - The 8th Workshop on MIning DAta for financial applicationS; Workshop on Advancements in Federated Learning.