This paper is concerned with the problem of predicting relative performance of classification algorithms. It focusses on methods that use results on small samples and discusses th...
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
Low overhead analysis of large distributed data sets is necessary for current data centers and for future sensor networks. In such systems, each node holds some data value, e.g., ...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...