Recent technology advances based on smart devices have improved the medical facilities and become increasingly popular in association with realtime health monitoring and remote/personals health-care. Healthcare organisations are still required to pay more attention for some improvements in terms of cost-effectiveness and maintaining efficiency, and avoid patients to take admission at hospital. ...

The dependency on the quality of the training data has led to significant work in noise reduction for instance-based learning algorithms. This paper presents an empirical evaluation of current noise reduction techniques, not just from the perspective of their comparative performance, but from the perspective of investigating the types of instances that they focus on for removal. A novel instanc...

Allomorphy is a phenomenon that occurs in many languages. Several psycholinguistic studies have shown that allomorphy, if present, co-determines cognitive processing. In the present paper we discussed allomorphic variations of Serbian instrumental singular form of pseudo-nouns as emerging from analogical learning. We compared the predictions derived from memory-based language processing models ...

Multiple instance learning (MIL) is concerned with learning from sets (bags) of objects (instances), where the individual instance labels are ambiguous. In this setting, supervised learning cannot be applied directly. Often, specialized MIL methods learn by making additional assumptions about the relationship of the bag labels and instance labels. Such assumptions may fit a particular dataset, ...

In our prior work, we introduced a generalization of the multiple-instance learning (MIL) model in which a bag’s label is not based on a single instance’s proximity to a single target point. Rather, a bag is positive if and only if it contains a collection of instances, each near one of a set of target points. This generalized model is much more expressive than the conventional multipleinstance...