Multiple Instance Learning
In multiple instance learning (MIL), instead of the instances, there are bags and each bag has certain number of instances. Given the bags with class labels, aim of MIL is to classify bags with potentially unlabeled instances. To learn a classifier at bag-level, bags can be encoded by using their instance frequencies in specific regions of the data space.
Emel Şeyma Küçükaşcı has been working on bag-level encoding algorithms and mathematical modeling strategies for MIL problems under my supervision. Details about her work can be reached on her web page.