In open-world semi-supervised learning, a machine learning model is task...
Partial Label Learning (PLL) is a type of weakly supervised learning whe...
Partial-label learning is a popular weakly supervised learning setting t...
In many real-world tasks, the concerned objects can be represented as a
...
In partial label learning (PLL), each training sample is associated with...
Label noise widely exists in large-scale datasets and significantly
dege...
Weakly Supervised Object Detection (WSOD) enables the training of object...
Complementary label learning (CLL) requires annotators to give
irrelevan...
Weakly supervised machine learning algorithms are able to learn from
amb...
Multi-label learning has attracted significant attention from both acade...
Exploiting label correlations is important to multi-label classification...
Multi-label learning (MLL) learns from the examples each associated with...
Although humans can easily identify the object of interest from groups o...
Partial label learning (PLL) is a typical weakly supervised learning pro...
Deep neural networks have been shown to be very powerful methods for man...
Ensemble learning aims to improve generalization ability by using multip...