Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification (2022)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; ALCOBAÇA NETO, EDESIO PINTO DE SOUZA - ICMC
- Unidade: ICMC
- Assunto: APRENDIZADO COMPUTACIONAL
- Keywords: Automated Machine Learning; meta-learning; competition
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: Microtome Publishing
- Publisher place: Brookline
- Date published: 2022
- Source:
- Título: Proceedings of Machine Learning Research : PMLR
- ISSN: 1938-7228
- Volume/Número/Paginação/Ano: v. 176, p. 80-96, 2022
- Conference titles: Conference on Neural Information Processing Systems - NeurIPS
-
ABNT
BAZ, Adrian El et al. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v176/el-baz22a.html. Acesso em: 27 dez. 2025. , 2022 -
APA
Baz, A. E., Ullah, I., Alcobaça, E., Carvalho, A. C. P. de L. F. de, Chen, H., Ferreira, F., et al. (2022). Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. Proceedings of Machine Learning Research : PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v176/el-baz22a.html -
NLM
Baz AE, Ullah I, Alcobaça E, Carvalho ACP de LF de, Chen H, Ferreira F, Gouk H, Guan C, Guyon I, Hospedales T, Hu S, Huisman M, Hutter F, Liu Z, Mohr F, Öztürk E, Rijn JN van, Sun H, Wang X, Zhu W. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 176 80-96.[citado 2025 dez. 27 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.html -
Vancouver
Baz AE, Ullah I, Alcobaça E, Carvalho ACP de LF de, Chen H, Ferreira F, Gouk H, Guan C, Guyon I, Hospedales T, Hu S, Huisman M, Hutter F, Liu Z, Mohr F, Öztürk E, Rijn JN van, Sun H, Wang X, Zhu W. Lessons learned from the NeurIPS 2021 MetaDL challenge: backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification [Internet]. Proceedings of Machine Learning Research : PMLR. 2022 ; 176 80-96.[citado 2025 dez. 27 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.html - A literature review on automated machine learning
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