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Mar 24, 2024 · This module effectively transmits the essence of similarity knowledge from the label space to the feature space, thereby amplifying ...
Partial label learning (PLL) refers to the classification task where each training instance is ambiguously annotated with a set of candidate labels.
Mar 28, 2024 · This module effectively transmits the essence of similarity knowledge from the label space to the feature space, thereby amplifying ...
My primary research interest lies in the field of trustworthy weakly supervised learning, . Specially now I am focusing on partial label learning, dataset ...
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Oct 25, 2021 · Partial label learning (PLL) is a typical weakly supervised learning problem, where each training example is associated with a set of candidate ...
Missing: Distilling Reliable Knowledge
This is the implemention of our AAAI'24 paper (Distilling Reliable Knowledge for Instance-dependent Partial Label Learning). Python 2 · LMNL LMNL Public.
Jun 10, 2024 · Partial label learning (PLL) is a typical weakly supervised learning problem, where each training example is associated with a set of ...
2023. Partial Label Learning with Emerging New Labels. XR Yu, DB Wang, ML ... Distilling Reliable Knowledge for Instance-dependent Partial Label Learning.
My research interests mainly include artificial intelligence, machine learning and data mining. I'm currently working on weakly supervised learning and ...