Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Abstract. In this paper we propose the extended star clustering algorithm and compare it with the original star clustering algorithm. We introduce a new concept of star and as a co...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
In traditional data clustering, similarity of a cluster of objects is measured by pairwise similarity of objects in that cluster. We argue that such measures are not appropriate f...