The basic idea is selecting from every training bag a pair of the most similar instances as instance prototypes and then mapping training bags into the ...
The basic idea is selecting from every training bag a pair of the most similar instances as instance prototypes and then mapping training bags into the ...
Multiple-Instance Learning (MIL) has attracted much attention of the machine learning community in recent years and many real-world ...
Sep 1, 2014 · Abstract Multiple-Instance Learning MIL has attracted much attention of the machine learning community in recent years and many real-world ...
Jan 19, 2023 · In this paper, we provide the first attempt to investigate MIL from only similar-dissimilar-unlabeled bags.
Sep 29, 2024 · We investigate a novel MIL problem about learning a bag-level binary classifier only from pairwise comparison bags.
Multiple-Instance Learning From Unlabeled Bags With Pairwise ...
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In multiple-instance learning (MIL), each training example is represented by a bag of instances. A training bag is either negative if it contains no positive ...
Mar 21, 2014 · The main idea is choosing a pair of instances with the highest or lowest similarity value depending on the bag label from every training bag and ...
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Oct 22, 2024 · To overcome this problem Yuan & Liu [17] proposed a model of pairwise similarity based instance reduction for Multiple Instance Learning (MIP).