Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
Most cost function based clustering or partitioning methods measure the compactness of groups of data. In contrast to this picture of a point source in feature space, some data sou...
PageRank is defined as the stationary state of a Markov chain obtained by perturbing the transition matrix of a web graph with a damping factor that spreads part of the rank. The...
Most existing semi-supervised learning methods are based on the smoothness assumption that data points in the same high density region should have the same label. This assumption, ...
A variational formulation of an image analysis problem has the nice feature that it is often easier to predict the eect of minimizing a certain energy functional than to interpret...