140 search results - page 4 / 28 » Dimensionality Reduction with Adaptive Kernels |
KDD
2007
ACM
14 years 5 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
VLDB
2007
ACM
14 years 5 months ago
2007
ACM
Abstract The notorious "dimensionality curse" is a wellknown phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approa...
NIPS
2008
13 years 6 months ago
2008
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
SIGMOD
2001
ACM
14 years 5 months ago
2001
ACM
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....