70 search results - page 10 / 14 » Multiple Kernel Learning for Dimensionality Reduction |
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Many clustering algorithms only find one clustering solution. However, data can often be grouped and interpreted in many different ways. This is particularly true in the high-dim...
ICML
2010
IEEE
13 years 8 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...
KDD
2007
ACM
14 years 7 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...
ICML
2009
IEEE
14 years 8 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...
ICRA
2007
IEEE
14 years 1 months ago
2007
IEEE
Abstract— The problem of an effective coordination of multiple autonomous robots is one of the most important tasks of the modern robotics. In turn, it is well known that the lea...