Hyperbolic secant representation of the logistic function: Application to probabilistic multiple instance learning for CT intracranial hemorrhage detection

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Bioengineering,
multiple instance learning   gaussian processes   bayesian variational inference   intracranial hemorrhage detection  

There has long been a problem of “weak supervision” in the field of artificial intelligence, where only part of the labels are observable in the training data, while the remaining labels are unknown. Multiple Instance Learning (MIL) is a paradigm to address this issue. In MIL, the training data is divided into multiple “bags”, each containing multi...