91 search results - page 15 / 19 » Kernel Dimensionality Reduction for Supervised Learning |
82
Voted
ICML
2010
IEEE
14 years 11 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
107
Voted
KDD
2007
ACM
15 years 10 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...
85
Voted
CVPR
2006
IEEE
16 years 9 days ago
2006
IEEE
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...
85
Voted
ICML
2009
IEEE
15 years 11 months ago
2009
IEEE
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
112
Voted
BMCBI
2010
14 years 10 months ago
2010
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...