332 search results - page 27 / 67 » On the Performance of Chernoff-Distance-Based Linear Dimensi... |
77
Voted
ICIAR
2004
Springer
15 years 3 months ago
2004
Springer
Previous work has shown that principal component analysis (PCA) of three-dimensional face models can be used to perform recognition to a high degree of accuracy. However, experimen...
CVPR
2005
IEEE
15 years 11 months ago
2005
IEEE
We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
98
Voted
KDD
2005
ACM
15 years 10 months ago
2005
ACM
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
74
Voted
DAGM
2006
Springer
15 years 1 months ago
2006
Springer
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
82
Voted
ICONIP
2007
14 years 11 months ago
2007
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...