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SLSFS
2005
Springer
13 years 10 months ago
Overview and Recent Advances in Partial Least Squares
Roman Rosipal, Nicole Krämer
SLSFS
2005
Springer
13 years 10 months ago
Is Feature Selection Still Necessary?
Amir Navot, Ran Gilad-Bachrach, Yiftah Navot, Naft...
SLSFS
2005
Springer
13 years 10 months ago
Constructing Visual Models with a Latent Space Approach
We propose the use of latent space models applied to local invariant features for object classification. We investigate whether using latent space models enables to learn patterns...
Florent Monay, Pedro Quelhas, Daniel Gatica-Perez,...
SLSFS
2005
Springer
13 years 10 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
13 years 10 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
13 years 10 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
13 years 10 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
13 years 10 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