Katalog der Deutschen Nationalbibliothek
Ergebnis der Suche nach: Malino*
Treffer 1 von 2739
|
|
| Link zu diesem Datensatz | https://d-nb.info/1390899632 |
| Titel | Advanced Analytics and Learning on Temporal Data : 10th ECML PKDD Workshop, AALTD 2025, Porto, Portugal, September 19, 2025, Revised Selected Papers / edited by Vincent Lemaire, Georgiana Ifrim, Anthony Bagnall, Simon Malinowski, Patrick Schäfer, Romain Tavenard |
| Person(en) |
Lemaire, Vincent (Herausgeber) Ifrim, Georgiana (Herausgeber) Bagnall, Anthony (Herausgeber) Malinowski, Simon (Herausgeber) Schäfer, Patrick (Herausgeber) Tavenard, Romain (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2026 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2026 |
| Umfang/Format | Online-Ressource, X, 215 p. 61 illus., 51 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-032-15534-4 Printed edition:: ISBN: 978-3-032-15536-8 |
| Inhalt | e-SMOTE: a train set rebalancing algorithm for time series classification -- The Next Motif: Tapping into Recurrence Dynamics and Precursor Signals to Forecast Events of Interest -- Re-framing Time Series Augmentation Through the Lens of Generative Models -- FuelCast: Benchmarking Tabular and Temporal Models for Ship Fuel Consumption -- MoTM: Towards a Foundation Model for Time Series Imputation based on Continuous Modeling -- A Deep Dive into Alternatives to the Global Average Pooling for Time Series Classification -- Adaptive Fine-Tuning via Pattern Specialization for Deep Time Series Forecasting -- Unsupervised Feature Construction for Time Series Anomaly Detection - An Evaluation -- Multi-output Ensembles for Multi-step Forecasting -- Time series extrinsic regression algorithms for forecasting long time series with a short horizon -- Towards a Library for the Analysis of Temporal Sequences -- FiTEM: Fine-tuning Time-series Foundation Models for Selective Forecasting -- T3A-LLM: A Two-Stage Temporal Knowledge Graph Alignment Method Enhanced by LLM |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2602210305531.354805982128 DOI: 10.1007/978-3-032-15535-1 |
| URL | https://doi.org/10.1007/978-3-032-15535-1 |
| ISBN/Einband/Preis | 978-3-032-15535-1 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Lecture Notes in Artificial Intelligence ; 16255 |
| Anmerkungen |
Hinweis zur Barrierefreiheit: PDF/UA-1 Hinweis zur Barrierefreiheit: Table of contents navigation Hinweis zur Barrierefreiheit: Single logical reading order Hinweis zur Barrierefreiheit: Short alternative textual descriptions Hinweis zur Barrierefreiheit: Use of color is not sole means of conveying information Hinweis zur Barrierefreiheit: Use of high contrast between text and background color Hinweis zur Barrierefreiheit: Next / Previous structural navigation Hinweis zur Barrierefreiheit: All non-decorative content supports reading without sight Hinweis zur Barrierefreiheit: Accessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupportspringernature.com. Please note that a more accessible version of this eBook is available as ePub Hinweis zur Barrierefreiheit: No reading system accessibility options actively disabled Hinweis zur Barrierefreiheit: Publisher contact for further accessibility information: accessibilitysupportspringernature.com |
| DDC-Notation | 006.31 (maschinell ermittelte DDC-Kurznotation) |
| Sachgruppe(n) | 004 Informatik |
| Online-Zugriff | Archivobjekt öffnen |
Treffer 1 von 2739
Administration
