779 search results - page 72 / 156 » Multi-Instance Dimensionality Reduction |
NIPS
2004
13 years 9 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 9 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 6 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...
AMC
2011
12 years 11 months ago
2011
：In this paper, a novel supervised dimensionality reduction method is developed based on both the correlation analysis and the idea of large margin learning. The method aims to m...
JMLR
2012
11 years 10 months ago
2012
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...