114 search results - page 12 / 23 » Nonlinear adaptive distance metric learning for clustering |
ALT
2003
Springer
13 years 11 months ago
2003
Springer
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
ICCV
2009
IEEE
15 years 14 days ago
2009
IEEE
Face identification is the problem of determining
whether two face images depict the same person or not.
This is difficult due to variations in scale, pose, lighting,
background...
CVPR
2006
IEEE
14 years 9 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
PAKDD
2009
ACM
14 years 2 months ago
2009
ACM
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...
DAGM
2011
Springer
12 years 7 months ago
2011
Springer
Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...