We address the problem of robust clustering by combining data partitions (forming a clustering ensemble) produced by multiple clusterings. We formulate robust clustering under an ...
We propose a novel method, called heterogeneous clustering ensemble (HCE), to generate robust clustering results that combine multiple partitions (clusters) derived from various cl...
Hye-Sung Yoon, Sang-Ho Lee, Sung-Bum Cho, Ju Han K...
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
—Handwritten text line segmentation on real-world data presents significant challenges that cannot be overcome by any single technique. Given the diversity of approaches and the...
Coreferencing entities across documents in a large corpus enables advanced document understanding tasks such as question answering. This paper presents a novel cross document core...
Jian Huang 0002, Sarah M. Taylor, Jonathan L. Smit...