750 search results - page 32 / 150 » Learning SVMs from Sloppily Labeled Data |
ML
2002
ACM
13 years 7 months ago
2002
ACM
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
ICPR
2006
IEEE
14 years 9 months ago
2006
IEEE
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
ICASSP
2010
IEEE
13 years 8 months ago
2010
IEEE
The goal of semi-supervised image segmentation is to obtain the segmentation from a partially labeled image. By utilizing the image manifold structure in labeled and unlabeled pix...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
BMCBI
2011
12 years 11 months ago
2011
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...