372 search results - page 6 / 75 » Covariance Kernels from Bayesian Generative Models |
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Point clouds are sets of points in two or three dimensions. Most kernel methods for learning on sets of points have not yet dealt with the specific geometrical invariances and pra...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Book
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
PPSN
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. Taking inspiration from approximate ranking, this paper investigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invarian...