SLSFS
2005
Springer
13 years 11 months ago
2005
Springer
We present a method which uses example pairs of equal or unequal class labels to select a subspace with near optimal metric properties in a kernel-induced Hilbert space. A represen...
SLSFS
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. Matrix factorization is a fundamental building block in many computer vision and machine learning algorithms. In this work we focus on the problem of ”structure from mo...
SLSFS
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-...
SLSFS
2005
Springer
13 years 11 months ago
2005
Springer
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
SLSFS
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. Mutual Information (MI) is a long studied measure of information content, and many attempts to apply it to feature extraction and stochastic coding have been made. Howeve...
PREMI
2005
Springer
13 years 11 months ago
2005
Springer
Images constitute data that lives in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from data of such high dimensions soon...
MCS
2005
Springer
13 years 11 months ago
2005
Springer
MCS
2005
Springer
13 years 11 months ago
2005
Springer
Abstract. Obtaining ground truth for hyperspectral data is an expensive task. In addition, a number of factors cause the spectral signatures of the same class to vary with location...
MCS
2005
Springer
13 years 11 months ago
2005
Springer
We have previously introduced the Learn++ algorithm that provides surprisingly promising performance for incremental learning as well as data fusion applications. In this contribut...
MCS
2005
Springer
13 years 11 months ago
2005
Springer
Mixed Group Ranks is a parametric method for combining rank based classi ers that is eective for many-class problems. Its parametric structure combines qualities of voting methods...