Learning about individuals from group statistics

Understand

We propose a new problem formulation which is similar to, but more informative than, the binary multiple-instance learning problem.

• In this setting, we are given groups of instances (described by feature vectors) along with estimates of the fraction of positively-labeled instances per group.
• The task is to learn an instance level classifier from this information.
• That is, we are trying to estimate the unknown binary labels of individuals from knowledge of group statistics.