— This paper proposes to incorporate bootstrap of data, random feature subspace and evolutionary algorithm with negative correlation learning to automatically design accurate and...
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
The aim of this paper is to present the design of a multimodal database suitable for research on new possibilities for automatic diagnosis of patients with severe obstructive slee...
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Abstract. Activity recognition has attracted increasing attention in recent years due to its potential to enable a number of compelling contextaware applications. As most approache...