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Carte Machine Learning and Knowledge Discovery in Databases. Research Track Bernhard Pfahringer

Machine Learning and Knowledge Discovery in Databases. Research Track

Autor: Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Joao Gama, Pedro H. Abreu
Limbă: engleză
Legare: Carte broșată
Editura: Springer-Verlag GmbH
Disponibilitate: La editor doar la comandă
Expediem în 17-27 zile
478.80 lei
This multi-volume set, LNAI 16013 to LNAI 16022, constitutes the refereed proceedings of the Europea...

Informații despre carte

Autor
Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Joao Gama, Pedro H. Abreu
Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2025
Pagini
632
EAN
9783032060952
ISBN
3032060958
Enbook ID
49478140
Editura
Springer-Verlag GmbH
Greutate
874
Dimensiuni
155 x 235

Descriere completă

This multi-volume set, LNAI 16013 to LNAI 16022, constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2025, held in Porto, Portugal, September 15 19, 2025.

The 300 full papers presented here, together with 15 demo papers, were carefully reviewed and selected from 1253 submissions. The papers presented in these proceedings are from the following three conference tracks:

  • The Research Track in Volume LNAI 16013-16020 refers about Anomaly & Outlier Detection, Bias & Fairness, Causality, Clustering, Data Challenges, Diffusion Models, Ensemble Learning, Graph Neural Networks, Graphs & Networks, Healthcare & Bioinformatics, Images & Computer Vision, Interpretability & Explainability, Large Language Models, Learning Theory, Multimodal Data, Neuro Symbolic Approaches, Optimization, Privacy & Security, Recommender Systems, Reinforcement Learning, Representation Learning, Resource Efficiency, Robustness & Uncertainty, Sequence Models, Streaming & Spatiotemporal Data, Text & Natural Language Processing, Time Series, and Transfer & Multitask Learning.
  • The Applied Data Science Track in Volume LNAI 16020-16022 refers about Agriculture, Food and Earth Sciences, Education, Engineering and Technology, Finance, Economy, Management or Marketing, Health, Biology, Bioinformatics or Chemistry, Industry (4.0, 5.0, Manufacturing, ...), Smart Cities, Transportation and Utilities (e.g., Energy), Sports, and Web and Social Networks
  • The Demo Track in LNAI 16022 showcased practical applications and prototypes, accepting 15 papers from a total of 30 submissions. These proceedings cover the papers accepted in the research and applied data science tracks.

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