In this paper we present the use of a "general purpose" textual entaiment recognizer in the Answer Validation Exercise (AVE) task. Our system has been developed to learn...
In response to the rapid development of DNA Microarray technology, many classification methods have been used for Microarray classification. SVMs, decision trees, Bagging, Boostin...
Hong Hu, Jiuyong Li, Ashley W. Plank, Hua Wang, Gr...
Large-scale biomedical data sets of macromolecular structures such as DNA and proteins describe highly complex biomolecular entities which often consist of thousands of atoms and ...
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
AiNet is an immune-inspired algorithm for data compression, i.e. the reduction of redundancy in data sets. In this paper we investigate the compression quality of aiNet. Therefore,...
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
Discovering frequent patterns from data is a popular exploratory technique in data mining. However, if the data are sensitive (e.g. patient health records, user behavior records) ...
Raghav Bhaskar, Srivatsan Laxman, Adam Smith, Abhr...
This paper presents a technique for visualizing large spatial data sets in Web Mapping Systems (WMS). The technique creates a hierarchical clustering tree, which is subsequently u...
Classification based on k-nearest neighbors (kNN classification) is one of the most widely used classification methods. The number k of nearest neighbors used for achieving a high ...