Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
In this paper, we propose an embedding method to seek an optimal low-dimensional manifold describing the intrinsical pose variations and to provide an identity-independent head pos...
Semi-supervised image segmentation is an important issue in many image processing applications, and has been a popular research area recently, the most popular are graph-based met...
In many real-world applications, such as image retrieval, it would be natural to measure the distances from one instance to others using instance specific distance which captures ...
Background: The most fundamental task using gene expression data in clinical oncology is to classify tissue samples according to their gene expression levels. Compared with tradit...