Sciweavers

SLSFS
2005
Springer
14 years 4 months ago
Generalization Bounds for Subspace Selection and Hyperbolic PCA
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...
Andreas Maurer
SLSFS
2005
Springer
14 years 4 months ago
Incorporating Constraints and Prior Knowledge into Factorization Algorithms - An Application to 3D Recovery
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...
Amit Gruber, Yair Weiss
SLSFS
2005
Springer
14 years 4 months ago
Discrete Component Analysis
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-...
Wray L. Buntine, Aleks Jakulin
SLSFS
2005
Springer
14 years 4 months ago
Random Projection, Margins, Kernels, and Feature-Selection
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...
Avrim Blum
SLSFS
2005
Springer
14 years 4 months ago
Auxiliary Variational Information Maximization for Dimensionality Reduction
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...
Felix V. Agakov, David Barber
PREMI
2005
Springer
14 years 4 months ago
Pattern Recognition in Video
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...
Rama Chellappa, Ashok Veeraraghavan, Gaurav Aggarw...
MCS
2005
Springer
14 years 4 months ago
Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data
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...
Suju Rajan, Joydeep Ghosh
MCS
2005
Springer
14 years 4 months ago
Ensemble Confidence Estimates Posterior Probability
We have previously introduced the Learn++ algorithm that provides surprisingly promising performance for incremental learning as well as data fusion applications. In this contribut...
Michael Muhlbaier, Apostolos Topalis, Robi Polikar
MCS
2005
Springer
14 years 4 months ago
A Probability Model for Combining Ranks
Mixed Group Ranks is a parametric method for combining rank based classiers that is eective for many-class problems. Its parametric structure combines qualities of voting methods...
Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang