In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
We propose a geometric constraint solving method based on connectivity analysis in graph theory, which can be used to decompose a well-constrained problem into some smaller ones i...
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
For more than a decade, the trend in geometric constraint systems solving has been to use a geometric decomposition/recombination approach. These methods are generally grounded on...
In this paper we propose a robust text segmentation method in complex background. The proposed method first utilizes the K-means algorithm to decompose a detected text block into ...