259 search results - page 38 / 52 » A Hybrid Convergent Method for Learning Probabilistic Networ... |
NIPS
2000
13 years 9 months ago
2000
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
BC
2006
13 years 7 months ago
2006
Recruitment learning in hierarchies is an inherently unstable process (Valiant, 1994). This paper presents conditions on parameters for a feedforward network to ensure stable recru...
PAMI
2006
13 years 7 months ago
2006
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
RECOMB
2000
Springer
13 years 11 months ago
2000
Springer
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
—The measure of similarity normally utilized in statistical signal processing is based on second order moments. In this paper, we reveal the probabilistic meaning of correntropy ...