Many existing spectral clustering algorithms share a conventional graph partitioning criterion: normalized cuts (NC). However, one problem with NC is that it poorly captures the g...
Classical studies of measuring image motion by computer have concentrated on the case of optical flow, in which there is a unique velocity near each point of the image. In [5], we...
Kernel learning plays an important role in many machine learning tasks. However, algorithms for learning a kernel matrix often scale poorly, with running times that are cubic in t...
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Despite the existence of obstacles in many database applications, traditional spatial query processing utilizes the Euclidean distance metric assuming that points in space are dire...
Jun Zhang, Dimitris Papadias, Kyriakos Mouratidis,...