Advances and Challenges in Meta-Learning: A Technical Review-Reference-Cited by-同舟云学术

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Advances and Challenges in Meta-Learning: A Technical Review

Published:2024-07 Issue:7 Volume:46 Page:4763-4779
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Vettoruzzo Anna¹^ORCID,Bouguelia Mohamed-Rafik¹^ORCID,Vanschoren Joaquin²^ORCID,Rögnvaldsson Thorsteinn¹^ORCID,Santosh KC³^ORCID

Affiliation:

1. Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden

2. Automated Machine Learning Group, Eindhoven University of Technology, Eindhoven, The Netherlands

3. Applied AI Research Lab, Department of Computer Science, University of South Dakota, Vermillion, SD, USA

Funder

Knowledge Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/34/10550108/10413635.pdf?arnumber=10413635

Reference202 articles.

1. AutoML to Date and Beyond: Challenges and Opportunities

2. Model-agnostic meta-learning for fast adaptation of deep networks;Finn

3. A survey of meta-reinforcement learning;Beck,2023

4. Meta-Learning

5. Meta-Learning in Neural Networks: A Survey

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1. Bayesian optimization-based Model-Agnostic Meta-Learning: Application to predict maximum cyclic moment resistance of steel bolted T-stub connections;Thin-Walled Structures;2024-11

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3. FSRM-DDIE : few-shot learning methods based on relation metrics for the prediction of drug-drug interaction events;Applied Intelligence;2024-09-10

4. Domain generalization through meta-learning: a survey;Artificial Intelligence Review;2024-09-09

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