As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Multiple-instance Learning (MIL) is a new paradigm
of supervised learning that deals with the classification of
bags. Each bag is presented as a collection of instances
from whi...
Zhouyu Fu (Australian National University), Antoni...
In region-based image annotation, keywords are usually associated with images instead of individual regions in the training data set. This poses a major challenge for any learning...
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...