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98
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CEC
2007
IEEE
15 years 6 months ago
Evolutionary random neural ensembles based on negative correlation learning
— This paper proposes to incorporate bootstrap of data, random feature subspace and evolutionary algorithm with negative correlation learning to automatically design accurate and...
Huanhuan Chen, Xin Yao
ASUNAM
2010
IEEE
15 years 2 months ago
Semi-Supervised Classification of Network Data Using Very Few Labels
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...
Frank Lin, William W. Cohen
85
Voted
LREC
2008
108views Education» more  LREC 2008»
15 years 1 months ago
Design of a Multimodal Database for Research on Automatic Detection of Severe Apnoea Cases
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...
Rubén Fernández Pozo, Luis A. Hern&a...
117
Voted
EMNLP
2007
15 years 2 months ago
Semi-Supervised Structured Output Learning Based on a Hybrid Generative and Discriminative Approach
This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
Jun Suzuki, Akinori Fujino, Hideki Isozaki
LOCA
2009
Springer
15 years 5 months ago
Activity Recognition from Sparsely Labeled Data Using Multi-Instance Learning
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...
Maja Stikic, Bernt Schiele