428 search results - page 25 / 86 » Preference learning with Gaussian processes |
108
Voted
ICASSP
2009
IEEE
15 years 9 months ago
2009
IEEE
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
107
Voted
PATAT
2004
Springer
15 years 8 months ago
2004
Springer
Abstract. Within the field of software agents, there has been increasing interest in automating the process of calendar scheduling in recent years. Calendar (or meeting) schedulin...
110
Voted
IJCNN
2008
IEEE
15 years 9 months ago
2008
IEEE
Abstract— Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrai...
118
Voted
ICA
2010
Springer
15 years 3 months ago
2010
Springer
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
123
Voted
CVPR
2007
IEEE
16 years 4 months ago
2007
IEEE
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...