Baz, Adrian El; Ullah, Ihsan; Alcobaça, Edesio 
; Carvalho, André Carlos Ponce de Leon Ferreira de ; Chen, Hong; Ferreira, Fábio; Gouk, Henry; Guan, Chaoyu; Guyon, Isabelle; Hospedales, Timothy; Hu, Shell; Huisman, Mike ; Hutter, Frank ; Liu, Zhengying; Mohr, Felix ; Öztürk, Ekrem ; Rijn, Jan N. van ; Sun, Haozhe; Wang, Xin; Zhu, Wenwu
Fonte: Proceedings of Machine Learning Research : PMLR. Nome do evento: Conference on Neural Information Processing Systems - NeurIPS. Unidade: ICMC
Assunto: APRENDIZADO COMPUTACIONAL
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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: 09 nov. 2024. , 2022APA
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.htmlNLM
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 2024 nov. 09 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.htmlVancouver
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 2024 nov. 09 ] Available from: https://proceedings.mlr.press/v176/el-baz22a.html
