- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Understanding transfer learning and gradient-based meta-learning techniques ; day:12 ; month:12 ; year:2023 ; pages:1-20
Machine learning ; (12.12.2023), 1-20
- Urheber
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s10994-023-06387-w
- URN
-
urn:nbn:de:101:1-2024022712473015447335
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 11:03 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Huisman, Mike
- Plaat, Aske
- Rijn, Jan N. van
- SpringerLink (Online service)
Ähnliche Objekte (12)
Generalized stochastic gradient learning
Improving heat transfer predictions in heterogeneous riparian zones using transfer learning techniques
Gradient-Based Competitive Learning: Theory
Understanding deep learning
Gradient estimation in dendritic reinforcement learning
Understanding recent deep‐learning techniques for identifying collective variables of molecular dynamics
End-to-end tire defect detection model based on transfer learning techniques
Evaluation of 4H‐SiC MOSFET transfer characteristics using machine‐learning techniques
Network Slicing with Reinforcement Learning and Transfer Learning
Maximizing reusability of learning objects through machine learning techniques
Introduction to Active Learning Techniques
Debugging learning algorithms : understanding and correcting machine learning models
Generalized stochastic gradient learning
Improving heat transfer predictions in heterogeneous riparian zones using transfer learning techniques
Gradient-Based Competitive Learning: Theory
Understanding deep learning
Gradient estimation in dendritic reinforcement learning
Understanding recent deep‐learning techniques for identifying collective variables of molecular dynamics
End-to-end tire defect detection model based on transfer learning techniques
Evaluation of 4H‐SiC MOSFET transfer characteristics using machine‐learning techniques
Network Slicing with Reinforcement Learning and Transfer Learning
Maximizing reusability of learning objects through machine learning techniques
Introduction to Active Learning Techniques
Debugging learning algorithms : understanding and correcting machine learning models
Generalized stochastic gradient learning
Improving heat transfer predictions in heterogeneous riparian zones using transfer learning techniques
Gradient-Based Competitive Learning: Theory
Understanding deep learning
Gradient estimation in dendritic reinforcement learning
Understanding recent deep‐learning techniques for identifying collective variables of molecular dynamics
End-to-end tire defect detection model based on transfer learning techniques
Evaluation of 4H‐SiC MOSFET transfer characteristics using machine‐learning techniques
Network Slicing with Reinforcement Learning and Transfer Learning
Maximizing reusability of learning objects through machine learning techniques
Introduction to Active Learning Techniques