Machine learning and knowledge discovery in databases Part 5 Research track
Robustness.- Time Series.- Transfer and Multitask Learning.
Gespeichert in:
| Körperschaft: | |
|---|---|
| Weitere Verfasser: | , , , , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Cham
Springer
2023
|
| Schriftenreihe: | Lecture notes in computer science
14173 |
| Schlagworte: |
Artificial intelligence
> Bildverarbeitung
> COMPUTERS / Artificial Intelligence
> COMPUTERS / Computer Vision & Pattern Recognition
> COMPUTERS / Networking / General
> COMPUTERS / Programming / Software Development
> COMPUTERS / Social Aspects / Human-Computer Interaction
> Computer networking & communications
> Computer vision
> Computerhardware
> Information technology: general issues
> Informationstechnik (IT), allgemeine Themen
> Künstliche Intelligenz
> Software Engineering
> Konferenzschrift
|
| Online Zugang: | Cover Inhaltsverzeichnis |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Tag hinzufügen 
| Zusammenfassung: | Robustness.- Time Series.- Transfer and Multitask Learning. 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 |
|---|---|
| Beschreibung: | Literaturangaben |
| Beschreibung: | liii, 460 Seiten Diagramme |
| ISBN: | 9783031434235 978-3-031-43423-5 |