AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework fo...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
In this paper, I will show how a controlled natural language can be used to describe knowledge for the Semantic Web and discuss the formal properties of this language. At the firs...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
: In a canonical genetic algorithm, the reproduction operators (crossover and mutation) are random in nature. The direction of the search carried out by the GA system is driven pur...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Text documents have sparse data spaces, and nearest neighbors may belong to different classes when using current existing proximity measures to describe the correlation ...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
This paper deals with the load-balancing of machines in a real-world job-shop scheduling problem, with identical machines. The load-balancing algorithm allocates jobs, split into l...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...