Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
We introduce a family of kernels on discrete data structures within the general class of decomposition kernels. A weighted decomposition kernel (WDK) is computed by dividing objec...
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Following (Blitzer et al., 2006), we present an application of structural correspondence learning to non-projective dependency parsing (McDonald et al., 2005). To induce the corre...