37 search results - page 6 / 8 » The Minimum Information Principle for Discriminative Learnin... |
IJAR
2010
13 years 6 months ago
2010
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
JMLR
2002
13 years 7 months ago
2002
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
ICIP
1995
IEEE
14 years 9 months ago
1995
IEEE
Traditionally, Markov models have not been successfully used for compression of signal data other than binary image data. Due to the fact that exact substring matches in non-binar...
BMCBI
2008
13 years 7 months ago
2008
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
CVPR
2010
IEEE
14 years 3 months ago
2010
IEEE
Due to the lack of explicit spatial consideration, existing
epitome model may fail for image recognition and target detection,
which directly motivates us to propose the so-calle...