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This paper proposes a new transductive learning method that integrates information propagation and prototype rectification in few-shot learning
This paper proposes a new transductive learning method that integrates information propagation and prototype rectification in few-shot learning.
We further reveal that current transductive few-shot learning models often assume the datasets have balanced classes, which cannot be guaranteed in practice. We ...
This paper proposes a new transductive learning method that integrates information propagation and prototype rectification in few-shot learning, which achieves ...
This paper proposes a new transductive learning method that integrates information propagation and prototype rectification in few-shot learning, which achieves ...
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Compared with inductive few-shot learning, transductive models typically perform better as they leverage all samples of the query set.
Missing: structure | Show results with:structure
Apr 23, 2023 · Compared with inductive few-shot learning, transductive models typically perform better as they leverage all samples of the query set.
Missing: structure | Show results with:structure
Oct 31, 2022 · This work proposes to conduct graph few-shot learning via constructing a task-specific structure for each meta-task.
Aug 4, 2020 · In few-shot learning, transductive algorithms make use of all the queries in an episode instead of treating them individually. One possible ...
In this paper, we propose a new weighted prototype network for few-shot learning. Our model consists of two modules, feature extraction and prototype ...