Semi-supervised learning methods exploit both labeled and unlabeled data items in their training process, requiring only a small subset of labeled items. Although capable of drastically reducing the costs of labeling ...

Semi-supervised learning methods exploit both labeled and unlabeled data items in their training process, requiring only a small subset of labeled items. Although capable of drastically reducing the costs of labeling ...

Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two ...

Semi-supervised learning techniques have gained increasing attention in the machine learning community, as a result of two main factors: (1) the available data is exponentially increasing; (2) the task of data labeling is ...

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not ...

In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the ...

In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the ...

Abstract. The meaning of such verb-noun collocations as the wind blows, time flies, the day passes by can be generalized as ‘what is designated by the noun exists’. Likewise, the meaning of make a decision, provide support, ...