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...
In this paper we propose an efficient algorithm for reducing a large mixture of Gaussians into a smaller mixture while still preserving the component structure of the original mod...
We present a novel OCR error correction method for languages without word delimiters that have a large character set, such as Japanese and Chinese. It consists of a statistical OC...
The paper proposes an efficient terminal and model order reduction method for compact modeling of interconnect circuits with many terminals. The new method is inspired by the rece...
Pu Liu, Sheldon X.-D. Tan, Boyuan Yan, Bruce McGau...
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...