In this paper, we investigate the role of a biomedical dataset on the classification accuracy of an algorithm. We quantify the complexity of a biomedical dataset using five complex...
We propose reliable outdoor object detection on mobile phone imagery from off-the-shelf devices. With the goal to provide both robust object detection and reduction of computation...
Clustered graph is a very useful model for drawing large and complex networks. This paper presents a new method for drawing clustered graphs in three dimensions. The method uses a ...
Convolution kernels, constructed by convolution of sub-kernels defined on sub-structures of composite objects, are widely used in classification, where one important issue is to ch...
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...