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View all- Tariq M(2024)Online and Self-Paced Learning Using AIAI-Driven Learning and Engagement in Higher Education10.4018/979-8-3693-4074-5.ch009(223-246)Online publication date: 25-Sep-2024
Multi-label learning aims to solve classification problems where instances are associated with a set of labels. In reality, it is generally easy to acquire unlabeled data but expensive or time-consuming to label them, and this ...
The scarcity of labeled data is a critical obstacle to deep learning. Semi-supervised learning (SSL) provides a promising way to leverage unlabeled data by pseudo labels. However, when the size of labeled data is very small (say a few labeled samples per ...
In semi-supervised learning, co-training is successfully in augmenting the training data with predicted pseudo-labels. With two independently trained regressors, a co-trainer iteratively exchanges their selected instances coupled with pseudo-...
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