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- Steve B. Cousins, Mark E. Frisse, W Chen, Charles N. Mead
- Proceedings. Symposium on Computer Applications…
- 1991

One of the barriers to using belief networks for medical information retrieval is the computational cost of reasoning as the networks become large. Stochastic simulation algorithms allow one to compute approximations of probability values in a reasonable amount of time. We previously examined the performance of five stochastic simulation algorithms applied… (More)

In this project, we introduce some new algorithms that build an Image Annotation Engine via machine learning. We also consider new methods to improve such algorithms. Numerical experiments that provide empirical support to the theory is provided.

In this paper we present a new formulation of the Support Vector Machine for classifying data. It is based on development of ideas from methods of total least squares, in which error in measured data is incorporated in the model design. The new formulation studied is similar to the soft margin SVM, but has to be solved using nonlinear optimization rather… (More)

We propose a new formulation of the Support Vector Machine (SVM) for classifying genetic data. It is based on the development of ideas from the method of total least squares, in which assumed error in measured data are incorporated in the model design. For genetic data the number of features is always far greater than the sample size. Consequently, in our… (More)

In this project, we introduce some new algorithms that build an Image Annotation Engine via machine learning. We also consider new methods to improve such algorithms. Numerical experiments that provide empirical support to the theory is provided.

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