The law of path steering, as proposed by Accot and Zhai, describes a quantitative relationship between human temporal performance and the path’s spatial characteristics. The ste...
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...
Xiaoxiao Shi, Qi Liu, Wei Fan, Qiang Yang, Philip ...
Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications ...