The design of a good kernel is fundamental for knowledge discovery from graph-structured data. Existing graph kernels exploit only limited information about the graph structures bu...
This paper tackles the problem of fitting multiple instances of a model to data corrupted by noise and outliers. The proposed solution is based on random sampling and conceptual da...
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....
In this paper we introduce an adaptive technique for compressing small quantities of text which are organized as a rooted directed graph. We impose a constraint on the technique s...
In this paper, we propose a tree-structured multiclass classifier to identify annotations and overlapping text from machine printed documents. Each node of the tree-structured cla...