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pro vyhledávání: '"Rabadán, Miquel Martí i"'
We propose Dense FixMatch, a simple method for online semi-supervised learning of dense and structured prediction tasks combining pseudo-labeling and consistency regularization via strong data augmentation. We enable the application of FixMatch in se
Externí odkaz:
http://arxiv.org/abs/2210.09919
Autor:
Rabadán, Miquel Martí i, Bujwid, Sebastian, Pieropan, Alessandro, Azizpour, Hossein, Maki, Atsuto
Publikováno v:
Vol. 3 (2022): Proceedings of the Northern Lights Deep Learning Workshop 2022
Most semi-supervised learning methods over-sample labeled data when constructing training mini-batches. This paper studies whether this common practice improves learning and how. We compare it to an alternative setting where each mini-batch is unifor
Externí odkaz:
http://arxiv.org/abs/2201.00604