112 search results - page 11 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
EUROSSC
2008
Springer
13 years 10 months ago
2008
Springer
Abstract. This paper describes methods and sensor technology used to identify persons from their walking characteristics. We use an array of simple binary switch floor sensors to d...
ICML
2004
IEEE
14 years 2 months ago
2004
IEEE
This paper describes an e cient method for learning the parameters of a Gaussian process (GP). The parameters are learned from multiple tasks which are assumed to have been drawn ...
AIME
2009
Springer
14 years 1 months ago
2009
Springer
Abstract. Mechanical ventilation can cause severe lung damage by inadequate adjustment of the ventilator. We introduce a Machine Learning approach to predict the pressure-dependent...
ICASSP
2010
IEEE
13 years 9 months ago
2010
IEEE
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...