ECML
2006
Springer
14 years 24 days ago
2006
Springer
Abstract-- Text categorization is the task of assigning predefined categories to natural language text. With the widely used `bag of words' representation, previous researches...
ECML
2006
Springer
14 years 24 days ago
2006
Springer
This paper presents a decomposition method for efficiently constructing 1-norm Support Vector Machines (SVMs). The decomposition algorithm introduced in this paper possesses many d...
ECML
2006
Springer
14 years 24 days ago
2006
Springer
We propose preprocessing spectral clustering with b-matching to remove spurious edges in the adjacency graph prior to clustering. B-matching is a generalization of traditional maxi...
ECML
2006
Springer
14 years 24 days ago
2006
Springer
In this article, I will consider Markov Decision Processes with two criteria, each defined as the expected value of an infinite horizon cumulative return. The second criterion is e...
ECML
2006
Springer
14 years 24 days ago
2006
Springer
Abstract. This paper is about the evaluation of the results of clustering algorithms, and the comparison of such algorithms. We propose a new method based on the enrichment of a se...
ECML
2006
Springer
14 years 24 days ago
2006
Springer
ECML
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. Most classification methods assume that the samples are drawn independently and identically from an unknown data generating distribution, yet this assumption is violated ...
ECML
2006
Springer
14 years 2 months ago
2006
Springer
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
ECML
2006
Springer
14 years 2 months ago
2006
Springer
Nearest neighbor forecasting models are attractive with their simplicity and the ability to predict complex nonlinear behavior. They rely on the assumption that observations simila...
ECML
2006
Springer
14 years 2 months ago
2006
Springer
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...