137 search results - page 12 / 28 » Quantifying the Impact of Learning Algorithm Parameter Tunin... |
ROBOCUP
2004
Springer
14 years 1 months ago
2004
Springer
We show how to apply learning methods to two robotics problems, namely the optimization of the on-board controller of an omnidirectional robot, and the derivation of a model of the...
MICCAI
2003
Springer
14 years 9 months ago
2003
Springer
Abstract. We present a novel technique where a medical image segmentation system is evolved using genetic programming. The evolved system was trained on just 8 images outlined by a...
CIKM
2010
Springer
13 years 6 months ago
2010
Springer
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
NIPS
2008
13 years 10 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
CIARP
2007
Springer
14 years 2 months ago
2007
Springer
Segmentation through seeded region growing is widely used because it is fast, robust and free of tuning parameters. However, the seeded region growing algorithm requires an automat...