IDA
2010
Springer
13 years 7 months ago
2010
Springer
We propose a clustering algorithm that effectively utilizes feature order preferences, which have the form that feature s is more important than feature t. Our clustering formulati...
IDA
2010
Springer
13 years 7 months ago
2010
Springer
IDA
2010
Springer
13 years 7 months ago
2010
Springer
In this paper we introduce three alternative combinatorial formulations of the theory of evidence (ToE), by proving that both plausibility and commonality functions share the stru...
IDA
2010
Springer
13 years 7 months ago
2010
Springer
The accuracy of methods for the assessment of mammographic risk analysis is heavily related to breast tissue characteristics. Previous work has demonstrated considerable success i...
IDA
2010
Springer
13 years 7 months ago
2010
Springer
Insufficient training data is one of the major problems in neural network learning, because it leads to poor learning performance. In order to enhance an intelligent learning proc...
IDA
2010
Springer
13 years 7 months ago
2010
Springer
Stacking is a widely used technique for combining classifiers and improving prediction accuracy. Early research in Stacking showed that selecting the right classifiers, their par...
IDA
2010
Springer
13 years 7 months ago
2010
Springer
According to Koestler, the notion of a bisociation denotes a connection between pieces of information from habitually separated domains or categories. In this paper, we consider a ...
IDA
2010
Springer
13 years 7 months ago
2010
Springer
Data-driven knowledge discovery is becoming a new trend in various scientific fields. In light of this, the goal of the present paper is to introduce a novel framework to study one...
ICONIP
2010
13 years 7 months ago
2010
Abstract. Reservoir computing approaches have been successfully applied to a variety of tasks. An inherent problem of these approaches, is, however, their variation in performance ...
ICONIP
2010
13 years 7 months ago
2010
Abstract. In this paper, we propose a novel approach for adaptive control of robotic manipulators. Our approach uses a representation of inverse dynamics models learned from a vari...