While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
An implicit assumption of many machine learning algorithms is that all attributes are of the same importance. An algorithm typically selects attributes based solely on their statis...
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
This paper describes ongoing research into the application of machine learning techniques for improving access to governmental information in complex digital libraries. Under the ...
Miles Efron, Jonathan L. Elsas, Gary Marchionini, ...
- The problem of stochastic sequential machines (SSM) synthesis is addressed and its relationship with the constrained sequence generation problem which arises during power estimat...