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Learning with noisy labels means When we say "noisy labels," we mean that an adversary has intentionally messed up the labels, which would have come from a "clean" distribution otherwise. This setting can also be used to cast learning from only positive and unlabeled data.
Jun 13, 2016 · I'm trying to train a neural network for classification, but the labels I have are rather noisy (around 30% of the labels are wrong).
Apr 5, 2024 · In this survey, we first comprehensively review the evolution of different deep learning approaches for noisy label combating in the image classification task.
In this paper, we theoretically study the problem of binary classification in the presence of random classification noise — the learner, instead of seeing the ...
Recent studies have shown that label noise can significantly impact the performance of deep learning models in many machine learning and computer vision ...
Recent studies have shown that label noise can significantly impact the performance of deep learning models in many machine learning and computer vision ...
A curated list of resources for Learning with Noisy Labels - subeeshvasu/Awesome-Learning-with-Label-Noise.
Aug 29, 2022 · I work in computer vision but I'd really be interested to read about such results in any domain of deep learning. Upvote 5. Downvote 8 Go to ...
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Aug 19, 2020 · A simple way to deal with noisy labels is to fine-tune a model that is pre-trained on clean datasets, like ImageNet. The better the pre-trained ...
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Managing noisy labels is a long-standing issue; therefore, we review the basic conventional approaches and theoretical foundations underlying robust deep ...
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