3006 search results - page 94 / 602 » Dimensionality reduction and generalization |
ESANN
2007
13 years 11 months ago
2007
Local algorithms for non-linear dimensionality reduction [1], [2], [3], [4], [5] and semi-supervised learning algorithms [6], [7] use spectral decomposition based on a nearest neig...
IJCAI
2007
13 years 11 months ago
2007
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
NIPS
2004
13 years 11 months ago
2004
This paper investigates the effect of Kernel Principal Component Analysis (KPCA) within the classification framework, essentially the regularization properties of this dimensional...
NIPS
1997
13 years 11 months ago
1997
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
CORR
2010
Springer
13 years 8 months ago
2010
Springer
This paper discusses the topic of dimensionality reduction for k-means clustering. We prove that any set of n points in d dimensions (rows in a matrix A ∈ Rn×d ) can be project...