1427 search results - page 120 / 286 » Learning with Annotation Noise |
146
Voted
ICPR
2002
IEEE
16 years 4 months ago
2002
IEEE
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
122
Voted
IJCAI
2001
15 years 5 months ago
2001
Successful image reconstruction requires the recognition of a scene and the generation of a clean image of that scene. We propose to use recurrent neural networks for both analysi...
135
Voted
NIPS
2004
15 years 5 months ago
2004
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
141
Voted
DSMML
2004
Springer
15 years 9 months ago
2004
Springer
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
109
Voted
NIPS
2000
15 years 5 months ago
2000
The principle of maximizing mutual information is applied to learning overcomplete and recurrent representations. The underlying model consists of a network of input units driving...