The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
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...
- As an alternative to traditional Evolutionary Algorithms (EAs), Population-Based Incremental Learning (PBIL) maintains a probabilistic model of the best individual(s). Originally...
Online multiplicative weight-update learning algorithms, such as Winnow, have proven to behave remarkably for learning simple disjunctions with few relevant attributes. The aim of ...
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...