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Learning with noisy labels

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.

Papers

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Showing 101–110 of 249 papers

TitleStatusHype
Improving Image Recognition by Retrieving from Web-Scale Image-Text Data—0
A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels—0
Identifiability of Label Noise Transition Matrix—0
How To Prevent the Continuous Damage of Noises To Model Training?—0
Cooperative Learning for Noisy Supervision—0
A Gradient-based Approach for Online Robust Deep Neural Network Training with Noisy Labels—0
Learning with Noisy Labels over Imbalanced Subpopulations—0
Jump-teaching: Ultra Efficient and Robust Learning with Noisy Label—0
Can Label-Noise Transition Matrix Help to Improve Sample Selection and Label Correction?—0
High-dimensional Learning with Noisy Labels—0
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