We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) op...
In this paper, we propose a novel technique for the efficient prediction of multiple continuous target variables from high-dimensional and heterogeneous data sets using a hierarch...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
In this paper we explore the effectiveness of three clustering methods used to perform word image indexing. The three methods are: the Self-Organazing Map (SOM), the Growing Hiera...