Machine learning and knowledge discovery in databases : Research track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings. Part I / Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi, editors.
ECML PKDD (Conference) (2023 : Turin, Italy); Koutra, Danai, editor.; Plant, Claudia, editor.; Gomez Rodriguez, Manuel, editor.; Baralis, Elena, editor.; Bonchi, Francesco, editor.
2023
Q325.5
Available Online

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Title Machine learning and knowledge discovery in databases : Research track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings. Part I / Danai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi, editors.
Meeting Name ECML PKDD (Conference) (2023 : Turin, Italy)
ISBN 9783031434129 (electronic bk.)
3031434129 (electronic bk.)
9783031434112
DOI https://doi.org/10.1007/978-3-031-43412-9
Published Cham : Springer, 2023.
Language English
Description 1 online resource (lv, 761 pages) : illustrations (some color).
Item Number 10.1007/978-3-031-43412-9 doi
Call Number Q325.5
Dewey Decimal Classification 006.3/1
Summary The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: Robustness; Time Series; Transfer and Multitask Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.
Note Includes author index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed September 20, 2023).
Added Author Koutra, Danai, editor.
Plant, Claudia, editor.
Gomez Rodriguez, Manuel, editor.
Baralis, Elena, editor.
Bonchi, Francesco, editor.
Series Lecture notes in computer science. Lecture notes in artificial intelligence.
Lecture notes in computer science ; 14169.
LNCS sublibrary. SL 7, Artificial intelligence.
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Active Learning
Adversarial Machine Learning
Anomaly Detection
Applications
Bayesian Methods
Causality
Clustering.

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