5 search results - page 1 / 1 » Bayesian inference for transductive learning of kernel matri... |
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
In kernel methods, an interesting recent development seeks to learn a good kernel from empirical data automatically. In this paper, by regarding the transductive learning of the k...
ML
2006
ACM
13 years 4 months ago
2006
ACM
This paper addresses the problem of transductive learning of the kernel matrix from a probabilistic perspective. We define the kernel matrix as a Wishart process prior and construc...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
NIPS
2008
13 years 5 months ago
2008
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
BMCBI
2007
13 years 4 months ago
2007
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...