ECML
2001
Springer
13 years 9 months ago
2001
Springer
Conventional work on scienti c discovery such as BACON derives empirical law equations from experimental data. In recent years, SDS introducing mathematical admissibility constrain...
ECML
2001
Springer
13 years 9 months ago
2001
Springer
Labeled data for classification could often be obtained by sampling that restricts or favors choice of certain classes. A classifier trained using such data will be biased, resulti...
ECML
2001
Springer
13 years 9 months ago
2001
Springer
ECML
2001
Springer
13 years 9 months ago
2001
Springer
Abstract. This paper presents a simple unsupervised learning algorithm for recognizing synonyms, based on statistical data acquired by querying a Web search engine. The algorithm, ...
ECML
2001
Springer
13 years 9 months ago
2001
Springer
ECML
2001
Springer
13 years 9 months ago
2001
Springer
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these...
ECML
2001
Springer
13 years 9 months ago
2001
Springer
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speci...
ECML
2001
Springer
13 years 9 months ago
2001
Springer
Solomonoff’s uncomputable universal prediction scheme ξ allows to predict the next
ECML
2001
Springer
13 years 9 months ago
2001
Springer
ECML
2001
Springer
13 years 9 months ago
2001
Springer
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...