Multi-Instance Learning

Multi-instance learning with discriminative bag mapping
Multi-instance learning (MIL) is a useful tool for tackling labeling ambiguity in learning because it allows a bag of instances to …
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Boosting for multi-graph classification
In this paper, we formulate a novel graph-based learning problem, multi-graph classification (MGC), which aims to learn a classifier …
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Exploring features for complicated objects: cross-view feature selection for multi-instance learning
In traditional multi-instance learning (MIL), instances are typically represented by using a single feature view. As MIL becoming …
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